diff --git a/cjs.py b/cjs.py index 5abe3b4..88b2215 100644 --- a/cjs.py +++ b/cjs.py @@ -25,16 +25,16 @@ def sum_P(bin, maxes): def sum_PlogP(sorted_bin, maxes): - maxes_ = maxes.transpose() - bin_ = sorted_bin.reset_index(drop=True) - count = bin_.shape[0] + maxes = maxes.transpose() + sorted_bin = sorted_bin.reset_index(drop=True) + count = sorted_bin.shape[0] if count == 0: return pd.Series([0 for i in range(maxes.shape[0])]) cum = np.array([(i + 1) for i in range(count)]) - return (pd.concat([bin_.loc[1:], maxes_], ignore_index=True, axis=0) - bin_).transpose() \ + return (pd.concat([sorted_bin.loc[1:], maxes], ignore_index=True, axis=0) - sorted_bin).transpose() \ .dot(cum * (np.log2(cum) - math.log(count, 2))) / count @@ -76,7 +76,7 @@ def compute_univariate_cjs(binA, binB, maxes): accepts bins of many dimensions, it returns a series of univariate CJS for each of the dimensions :param binA: :param binB: - :param maxes: + :param maxes: pd.Series :return: ''' if binA.shape[1] != binB.shape[1]: @@ -85,6 +85,7 @@ def compute_univariate_cjs(binA, binB, maxes): # - done for the parallel computation for all the dimensions ind_sorted_binA = ind_sort(binA) ind_sorted_binB = ind_sort(binB) + maxes = maxes.to_frame() CJSs = sum_PlogP(ind_sorted_binA, maxes) \ - sum_PlogPQ(binA, binB, maxes) \ @@ -96,13 +97,13 @@ def compute_cond_CJS(binA, binB, binA_point_ids, binB_point_ids, I1, I2, maxes, if len(I1) != len(I2): raise ValueError - maxes_ = maxes.loc[dim].to_frame() + max = pd.Series(maxes[dim]) total_binA_points_count = len(binA_point_ids) if 0 == total_binA_points_count: return 0 return sum([len(binA_point_ids.intersection(I1[i])) / total_binA_points_count * compute_univariate_cjs(binA.loc[binA_point_ids.intersection(I1[i]), dim].to_frame(), - binB.loc[binB_point_ids.intersection(I2[i]), dim].to_frame(), maxes_)[0] + binB.loc[binB_point_ids.intersection(I2[i]), dim].to_frame(), max)[0] for i in range(len(I1))]) @@ -181,17 +182,31 @@ def extend_I(I, disc): return disc_ -def compute_CJS(init_binA, init_binB, maxes): +def compute_CJS(binA, binB, maxes): + ''' + main method to compute CJS + :param binA: + :param binB: + :param maxes: + :return: + ''' + if type(maxes) is not pd.Series: + raise ValueError("maxes should be of pd.Series type!") + if len(maxes) != len(binA.columns) or len(maxes) != len(binB.columns): + raise ValueError("For computing CJS bins should have the same number of dimensions as maxes!") # renaming relevant columns in the basic order - binA = init_binA.rename(columns={init_binA.columns[i]: i for i in range(len(init_binA.columns))}) - binB = init_binB.rename(columns={init_binB.columns[i]: i for i in range(len(init_binB.columns))}) + binA = binA.rename(columns={binA.columns[i]: i for i in range(len(binA.columns))}) + binB = binB.rename(columns={binB.columns[i]: i for i in range(len(binB.columns))}) + # reindexing maxes in the basic order + maxes = maxes.reset_index(drop=True) # fix missing values with mean value fix_missing_values(binA) fix_missing_values(binB) symm_cjs = _compute_CJS(binA, binB, maxes) + _compute_CJS(binB, binA, maxes) - normalization = sum(sum_P(binA, maxes)) + sum(sum_P(binB, maxes)) + maxes_frame = maxes.to_frame() + normalization = sum(sum_P(binA, maxes_frame)) + sum(sum_P(binB, maxes_frame)) return symm_cjs / normalization @@ -236,15 +251,15 @@ def _compute_CJS(binA, binB, maxes): binA = data.loc[[i for i in range(200)], attrs] binB = data.loc[[i for i in range(200, 400)], attrs] - print(str(compute_CJS(binA, binB, pd.DataFrame(np.max(data[attrs]).transpose().reset_index(drop=True))))) + print(str(compute_CJS(binA, binB, binA.max(0)[attrs]))) def compute_CJSs(bin_map, curr, data, dim_maxes): data_wo_curr = data.copy() data_wo_curr.pop(curr) - maxes_ = dim_maxes.drop(curr).to_frame().reset_index(drop=True) + dim_maxes = dim_maxes.drop(curr) - return compute_CJSs1(bin_map, data_wo_curr, maxes_) + return compute_CJSs1(bin_map, data_wo_curr, dim_maxes) def compute_CJSs1(bin_map, data_wo_curr, maxes_): diff --git a/correlation_measures/binning.py b/correlation_measures/binning.py index ad41bb0..1fcd0f9 100644 --- a/correlation_measures/binning.py +++ b/correlation_measures/binning.py @@ -33,7 +33,7 @@ def equal_frequency_binning_duplicate_drop(self): qcut = self._compute_qcut() # qcut = qcut.cat.remove_unused_categories() - bounds = [float(re.search(', (-*\d+\.*\d*)', c).group(1)) for c in qcut.cat.categories] + bounds = [float(re.search(', (-*\d+\.*\d*e*-*\d*)', c).group(1)) for c in qcut.cat.categories] # including global_min with a margin of 1 bounds.insert(0, self.global_min - 1) self.bounds = pd.Series(bounds) diff --git a/main.py b/main.py index 1668aba..3c718fe 100644 --- a/main.py +++ b/main.py @@ -2,8 +2,10 @@ import sys import datetime +import time # todo fix for server push import matplotlib + matplotlib.use('Agg') import matplotlib.pyplot as plt import numpy as np @@ -40,8 +42,6 @@ def write(log, *args): log.write('\n') - - def plot_distances(dir, distances): dim_count = len(distances) plt.figure(1) @@ -77,8 +77,17 @@ def compute_distances(bin_map, curr, data, dim_maxes, subspace = sm.greedy_topk(data, curr, k, cor_measure) elif method == cst.Method.HET_GREEDY_TOPK: subspace = sm.het_greedy_topk(data, curr, k, delta, cor_measure) + elif method == cst.Method.BEST_FIRST: + subspace = sm.best_first(data, curr, k, cor_measure) + elif method == cst.Method.BEAM_SEARCH: + subspace = sm.beam_search(data, curr, k, beam_width, cor_measure) + elif method == cst.Method.HET_BEAM_SEARCH: + subspace = sm.het_beam_search(data, curr, k, beam_width, delta, cor_measure) + else: + raise ValueError("there is no such method!") # todo the rest of the methods data = data.copy().loc[:, subspace] + dim_maxes = dim_maxes[subspace] return id.compute_IDs1(bin_map, data, dim_maxes) if distance_measure == cst.DistanceMeasure.ID \ else cjs.compute_CJSs1(bin_map, data, dim_maxes) @@ -86,6 +95,7 @@ def compute_distances(bin_map, curr, data, dim_maxes, def compute_optimal_discretization(data, method=cst.Method.ORIGINAL, cor_measure=None, distance_measure=cst.DistanceMeasure.ID, log=None): + start = time.time() # class labels are not of much use in original ipd.. class_labels = data.pop(data.shape[1] - 1) dim_count = data.shape[1] @@ -127,7 +137,7 @@ def compute_optimal_discretization(data, method=cst.Method.ORIGINAL, cor_measure # range(len(distances))], distances]) # todo python342 distancez.append([[data.loc[binning.rank_data[binning.rank_data[curr] - == math.floor(float(re.search(', (-*\d+\.*\d*)', + == math.floor(float(re.search(', (-*\d+\.*\d*e*-*\d*)', dist_bins[i]).group(1)))] .index.tolist()[0], curr] for i in range(len(distances))], distances]) @@ -171,6 +181,8 @@ def compute_optimal_discretization(data, method=cst.Method.ORIGINAL, cor_measure disc_macro_intervals.append(curr_macro_intervals) disc_points.append(curr_macro_points) + end = time.time() + write(log, end - start, 'seconds') return disc_macro_intervals, disc_points, class_labels, distancez @@ -190,10 +202,14 @@ def get_discretized_points(curr, data, discretizations, dist_bins, min_id, rank_ # todo python342 right = \ - data.loc[rank_data[rank_data[curr] == math.floor(float(re.search(', (-*\d+\.*\d*)', dist_bins[micro_bin_id]).group(1)))][curr].index[0]][curr] + data.loc[rank_data[rank_data[curr] == math.floor(float(re.search(', (-*\d+\.*\d*e*-*\d*)', + dist_bins[micro_bin_id]).group(1)))][ + curr].index[0]][curr] if not len(macro_interval): macro_interval.append( - data.loc[rank_data[rank_data[curr] == math.ceil(float(re.search('(-*\d+\.*\d*),', dist_bins[micro_bin_id]).group(1)))][curr].index[0]][ + data.loc[rank_data[rank_data[curr] == math.ceil(float(re.search('(-*\d+\.*\d*e*-*\d*),', + dist_bins[micro_bin_id]).group( + 1)))][curr].index[0]][ curr]) macro_interval.append(right) else: @@ -235,6 +251,8 @@ def get_discretized_points(curr, data, discretizations, dist_bins, min_id, rank_ method = cst.Method[method_arg[0].replace('-m=', '').upper()] if method_arg else cst.Method.ORIGINAL cor_measure = cst.CorrelationMeasure[corr_measure_arg[0].replace('-cor=', '').upper()] if corr_measure_arg \ else None + if method is not cst.Method.ORIGINAL and cor_measure is None: + raise ValueError('A correlation measure should be given!') distance_measure = cst.DistanceMeasure[ distance_measure_arg[0].replace('-dist=', '').upper()] if distance_measure_arg \ else cst.DistanceMeasure.ID @@ -263,13 +281,17 @@ def get_discretized_points(curr, data, discretizations, dist_bins, min_id, rank_ print('output files are:', dir + '*') log_file = dir + "log.txt" - with open(log_file, 'w') as log: - disc_intervals, disc_points, class_labels, distances = compute_optimal_discretization(data, method, - cor_measure, - distance_measure, log) + try: + with open(log_file, 'w') as log: + disc_intervals, disc_points, class_labels, distances = compute_optimal_discretization(data, method, + cor_measure, + distance_measure, log) - plot_distances(dir, distances) + plot_distances(dir, distances) - write_out_file(dir + cst.FILE_DATA_OUTPUT, disc_intervals, disc_points, class_labels) + write_out_file(dir + cst.FILE_DATA_OUTPUT, disc_intervals, disc_points, class_labels) - write_cut_file(dir + cst.FILE_DATA_CUTS, disc_intervals) + write_cut_file(dir + cst.FILE_DATA_CUTS, disc_intervals) + except: + print ("Error in " + dir + ":", sys.exc_info()[0]) + raise \ No newline at end of file diff --git a/run.sh b/run.sh index 63fe43d..df6a8cf 100644 --- a/run.sh +++ b/run.sh @@ -1,185 +1,914 @@ #!/usr/bin/env bash #storing the output files into logs3 directory +#======================GREEDY_TOPK====================== + +# -------------ID experiments------------- + +# ----original synthetic cases---- +#python main.py -f=synthetic_cases/synthetic_2d_parity_problem.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_3d_parity_problem.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_4d_parity_problem.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_5d_parity_problem.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_10d_parity_problem.csv -m=GREEDY_TOPK -cor=uds & +# +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_2.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_3.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_4.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_5.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_10.csv -m=GREEDY_TOPK -cor=uds & +# +## ----with added irrelevant features---- +# +#python main.py -f=synthetic_cases/synthetic_2d_parity_problem_1.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_2d_parity_problem_2.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_2d_parity_problem_3.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_2d_parity_problem_4.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_2d_parity_problem_5.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_2d_parity_problem_10.csv -m=GREEDY_TOPK -cor=uds & +# +#python main.py -f=synthetic_cases/synthetic_3d_parity_problem_1.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_3d_parity_problem_2.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_3d_parity_problem_3.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_3d_parity_problem_4.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_3d_parity_problem_5.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_3d_parity_problem_10.csv -m=GREEDY_TOPK -cor=uds & +# +#python main.py -f=synthetic_cases/synthetic_4d_parity_problem_1.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_4d_parity_problem_2.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_4d_parity_problem_3.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_4d_parity_problem_4.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_4d_parity_problem_5.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_4d_parity_problem_10.csv -m=GREEDY_TOPK -cor=uds & +# +#python main.py -f=synthetic_cases/synthetic_5d_parity_problem_1.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_5d_parity_problem_2.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_5d_parity_problem_3.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_5d_parity_problem_4.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_5d_parity_problem_5.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_5d_parity_problem_10.csv -m=GREEDY_TOPK -cor=uds & +# +#python main.py -f=synthetic_cases/synthetic_10d_parity_problem_1.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_10d_parity_problem_2.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_10d_parity_problem_3.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_10d_parity_problem_4.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_10d_parity_problem_5.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_10d_parity_problem_10.csv -m=GREEDY_TOPK -cor=uds & +# +# +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_1.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_2.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_3.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_4.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_5.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_10.csv -m=GREEDY_TOPK -cor=uds & +# +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_1.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_2.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_3.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_4.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_5.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_10.csv -m=GREEDY_TOPK -cor=uds & +# +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_1.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_2.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_3.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_4.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_5.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_10.csv -m=GREEDY_TOPK -cor=uds & +# +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_1.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_2.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_3.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_4.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_5.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_10.csv -m=GREEDY_TOPK -cor=uds & +# +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_1.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_2.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_3.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_4.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_5.csv -m=GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_10.csv -m=GREEDY_TOPK -cor=uds & + +# ----with added irrelevant features and proposed algorithms---- + +#todo add more commands + +# -------------CJS experiments------------- + +# ----original synthetic cases---- +python main.py -f=synthetic_cases/synthetic_2d_parity_problem.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & + +# ----with added irrelevant features---- + +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_1.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_2.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_3.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_4.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_5.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_10.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & + +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_1.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_2.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_3.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_4.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_5.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_10.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & + +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_1.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_2.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_3.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_4.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_5.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_10.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & + +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_1.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_2.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_3.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_4.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_5.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_10.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & + +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_1.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_2.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_3.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_4.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_5.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_10.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & + + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_1.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_2.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_3.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_4.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_5.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_10.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_1.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_2.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_3.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_4.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_5.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_10.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_1.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_2.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_3.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_4.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_5.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_10.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_1.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_2.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_3.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_4.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_5.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_10.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_1.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_2.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_3.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_4.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_5.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_10.csv -dist=CJS -m=GREEDY_TOPK -cor=uds & + +#======================HET_GREEDY_TOPK====================== + +# -------------ID experiments------------- + +## ----original synthetic cases---- +#python main.py -f=synthetic_cases/synthetic_2d_parity_problem.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_3d_parity_problem.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_4d_parity_problem.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_5d_parity_problem.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_10d_parity_problem.csv -m=HET_GREEDY_TOPK -cor=uds & +# +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_2.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_3.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_4.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_5.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_10.csv -m=HET_GREEDY_TOPK -cor=uds & +# +## ----with added irrelevant features---- +# +#python main.py -f=synthetic_cases/synthetic_2d_parity_problem_1.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_2d_parity_problem_2.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_2d_parity_problem_3.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_2d_parity_problem_4.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_2d_parity_problem_5.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_2d_parity_problem_10.csv -m=HET_GREEDY_TOPK -cor=uds & +# +#python main.py -f=synthetic_cases/synthetic_3d_parity_problem_1.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_3d_parity_problem_2.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_3d_parity_problem_3.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_3d_parity_problem_4.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_3d_parity_problem_5.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_3d_parity_problem_10.csv -m=HET_GREEDY_TOPK -cor=uds & +# +#python main.py -f=synthetic_cases/synthetic_4d_parity_problem_1.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_4d_parity_problem_2.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_4d_parity_problem_3.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_4d_parity_problem_4.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_4d_parity_problem_5.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_4d_parity_problem_10.csv -m=HET_GREEDY_TOPK -cor=uds & +# +#python main.py -f=synthetic_cases/synthetic_5d_parity_problem_1.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_5d_parity_problem_2.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_5d_parity_problem_3.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_5d_parity_problem_4.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_5d_parity_problem_5.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_5d_parity_problem_10.csv -m=HET_GREEDY_TOPK -cor=uds & +# +#python main.py -f=synthetic_cases/synthetic_10d_parity_problem_1.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_10d_parity_problem_2.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_10d_parity_problem_3.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_10d_parity_problem_4.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_10d_parity_problem_5.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_10d_parity_problem_10.csv -m=HET_GREEDY_TOPK -cor=uds & +# +# +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_1.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_2.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_3.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_4.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_5.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_10.csv -m=HET_GREEDY_TOPK -cor=uds & +# +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_1.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_2.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_3.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_4.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_5.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_10.csv -m=HET_GREEDY_TOPK -cor=uds & +# +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_1.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_2.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_3.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_4.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_5.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_10.csv -m=HET_GREEDY_TOPK -cor=uds & +# +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_1.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_2.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_3.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_4.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_5.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_10.csv -m=HET_GREEDY_TOPK -cor=uds & +# +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_1.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_2.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_3.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_4.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_5.csv -m=HET_GREEDY_TOPK -cor=uds & +#python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_10.csv -m=HET_GREEDY_TOPK -cor=uds & + +# ----with added irrelevant features and proposed algorithms---- + +#todo add more commands + +# -------------CJS experiments------------- + +# ----original synthetic cases---- +python main.py -f=synthetic_cases/synthetic_2d_parity_problem.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & + +# ----with added irrelevant features---- + +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_1.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_2.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_3.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_4.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_5.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_10.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & + +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_1.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_2.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_3.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_4.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_5.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_10.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & + +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_1.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_2.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_3.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_4.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_5.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_10.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & + +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_1.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_2.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_3.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_4.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_5.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_10.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & + +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_1.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_2.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_3.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_4.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_5.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_10.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & + + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_1.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_2.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_3.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_4.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_5.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_10.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_1.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_2.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_3.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_4.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_5.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_10.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_1.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_2.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_3.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_4.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_5.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_10.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_1.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_2.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_3.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_4.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_5.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_10.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_1.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_2.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_3.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_4.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_5.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_10.csv -dist=CJS -m=HET_GREEDY_TOPK -cor=uds & + +#======================BEST_FIRST====================== + +# -------------ID experiments------------- + +# ----original synthetic cases---- +python main.py -f=synthetic_cases/synthetic_2d_parity_problem.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem.csv -m=BEST_FIRST -cor=uds & + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10.csv -m=BEST_FIRST -cor=uds & + +# ----with added irrelevant features---- + +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_1.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_2.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_3.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_4.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_5.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_10.csv -m=BEST_FIRST -cor=uds & + +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_1.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_2.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_3.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_4.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_5.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_10.csv -m=BEST_FIRST -cor=uds & + +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_1.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_2.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_3.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_4.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_5.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_10.csv -m=BEST_FIRST -cor=uds & + +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_1.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_2.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_3.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_4.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_5.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_10.csv -m=BEST_FIRST -cor=uds & + +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_1.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_2.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_3.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_4.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_5.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_10.csv -m=BEST_FIRST -cor=uds & + + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_1.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_2.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_3.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_4.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_5.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_10.csv -m=BEST_FIRST -cor=uds & + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_1.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_2.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_3.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_4.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_5.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_10.csv -m=BEST_FIRST -cor=uds & + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_1.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_2.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_3.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_4.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_5.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_10.csv -m=BEST_FIRST -cor=uds & + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_1.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_2.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_3.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_4.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_5.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_10.csv -m=BEST_FIRST -cor=uds & + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_1.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_2.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_3.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_4.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_5.csv -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_10.csv -m=BEST_FIRST -cor=uds & + +# ----with added irrelevant features and proposed algorithms---- + +#todo add more commands + +# -------------CJS experiments------------- + +# ----original synthetic cases---- +python main.py -f=synthetic_cases/synthetic_2d_parity_problem.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem.csv -dist=CJS -m=BEST_FIRST -cor=uds & + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10.csv -dist=CJS -m=BEST_FIRST -cor=uds & + +# ----with added irrelevant features---- + +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_1.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_2.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_3.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_4.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_5.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_10.csv -dist=CJS -m=BEST_FIRST -cor=uds & + +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_1.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_2.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_3.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_4.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_5.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_10.csv -dist=CJS -m=BEST_FIRST -cor=uds & + +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_1.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_2.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_3.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_4.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_5.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_10.csv -dist=CJS -m=BEST_FIRST -cor=uds & + +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_1.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_2.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_3.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_4.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_5.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_10.csv -dist=CJS -m=BEST_FIRST -cor=uds & + +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_1.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_2.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_3.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_4.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_5.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_10.csv -dist=CJS -m=BEST_FIRST -cor=uds & + + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_1.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_2.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_3.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_4.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_5.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_10.csv -dist=CJS -m=BEST_FIRST -cor=uds & + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_1.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_2.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_3.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_4.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_5.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_10.csv -dist=CJS -m=BEST_FIRST -cor=uds & + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_1.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_2.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_3.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_4.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_5.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_10.csv -dist=CJS -m=BEST_FIRST -cor=uds & + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_1.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_2.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_3.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_4.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_5.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_10.csv -dist=CJS -m=BEST_FIRST -cor=uds & + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_1.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_2.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_3.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_4.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_5.csv -dist=CJS -m=BEST_FIRST -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_10.csv -dist=CJS -m=BEST_FIRST -cor=uds & + +#======================BEAM_SEARCH====================== + +# -------------ID experiments------------- + +# ----original synthetic cases---- +python main.py -f=synthetic_cases/synthetic_2d_parity_problem.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem.csv -m=BEAM_SEARCH -cor=uds & + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10.csv -m=BEAM_SEARCH -cor=uds & + +# ----with added irrelevant features---- + +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_1.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_2.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_3.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_4.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_5.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_10.csv -m=BEAM_SEARCH -cor=uds & + +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_1.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_2.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_3.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_4.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_5.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_10.csv -m=BEAM_SEARCH -cor=uds & + +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_1.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_2.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_3.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_4.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_5.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_10.csv -m=BEAM_SEARCH -cor=uds & + +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_1.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_2.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_3.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_4.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_5.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_10.csv -m=BEAM_SEARCH -cor=uds & + +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_1.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_2.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_3.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_4.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_5.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_10.csv -m=BEAM_SEARCH -cor=uds & + + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_1.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_2.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_3.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_4.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_5.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_10.csv -m=BEAM_SEARCH -cor=uds & + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_1.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_2.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_3.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_4.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_5.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_10.csv -m=BEAM_SEARCH -cor=uds & + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_1.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_2.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_3.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_4.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_5.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_10.csv -m=BEAM_SEARCH -cor=uds & + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_1.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_2.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_3.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_4.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_5.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_10.csv -m=BEAM_SEARCH -cor=uds & + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_1.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_2.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_3.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_4.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_5.csv -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_10.csv -m=BEAM_SEARCH -cor=uds & + +# ----with added irrelevant features and proposed algorithms---- + +#todo add more commands + +# -------------CJS experiments------------- + +# ----original synthetic cases---- +python main.py -f=synthetic_cases/synthetic_2d_parity_problem.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & + +# ----with added irrelevant features---- + +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_1.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_2.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_3.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_4.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_5.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_10.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & + +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_1.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_2.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_3.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_4.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_5.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_10.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & + +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_1.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_2.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_3.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_4.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_5.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_10.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & + +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_1.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_2.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_3.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_4.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_5.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_10.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & + +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_1.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_2.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_3.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_4.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_5.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_10.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & + + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_1.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_2.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_3.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_4.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_5.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_10.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_1.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_2.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_3.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_4.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_5.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_10.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_1.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_2.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_3.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_4.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_5.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_10.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_1.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_2.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_3.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_4.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_5.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_10.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_1.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_2.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_3.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_4.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_5.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_10.csv -dist=CJS -m=BEAM_SEARCH -cor=uds & + +#======================HET_BEAM_SEARCH====================== + # -------------ID experiments------------- # ----original synthetic cases---- -python main.py -f=synthetic_cases/synthetic_2d_parity_problem.csv & -python main.py -f=synthetic_cases/synthetic_3d_parity_problem.csv & -python main.py -f=synthetic_cases/synthetic_4d_parity_problem.csv & -python main.py -f=synthetic_cases/synthetic_5d_parity_problem.csv & -python main.py -f=synthetic_cases/synthetic_10d_parity_problem.csv & - -python main.py -f=synthetic_cases/synthetic_cube_in_cube_2.csv & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_3.csv & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_4.csv & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_5.csv & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_10.csv & +python main.py -f=synthetic_cases/synthetic_2d_parity_problem.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem.csv -m=HET_BEAM_SEARCH -cor=uds & + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10.csv -m=HET_BEAM_SEARCH -cor=uds & # ----with added irrelevant features---- -python main.py -f=synthetic_cases/synthetic_2d_parity_problem_1.csv & -python main.py -f=synthetic_cases/synthetic_2d_parity_problem_2.csv & -python main.py -f=synthetic_cases/synthetic_2d_parity_problem_3.csv & -python main.py -f=synthetic_cases/synthetic_2d_parity_problem_4.csv & -python main.py -f=synthetic_cases/synthetic_2d_parity_problem_5.csv & -python main.py -f=synthetic_cases/synthetic_2d_parity_problem_10.csv & - -python main.py -f=synthetic_cases/synthetic_3d_parity_problem_1.csv & -python main.py -f=synthetic_cases/synthetic_3d_parity_problem_2.csv & -python main.py -f=synthetic_cases/synthetic_3d_parity_problem_3.csv & -python main.py -f=synthetic_cases/synthetic_3d_parity_problem_4.csv & -python main.py -f=synthetic_cases/synthetic_3d_parity_problem_5.csv & -python main.py -f=synthetic_cases/synthetic_3d_parity_problem_10.csv & - -python main.py -f=synthetic_cases/synthetic_4d_parity_problem_1.csv & -python main.py -f=synthetic_cases/synthetic_4d_parity_problem_2.csv & -python main.py -f=synthetic_cases/synthetic_4d_parity_problem_3.csv & -python main.py -f=synthetic_cases/synthetic_4d_parity_problem_4.csv & -python main.py -f=synthetic_cases/synthetic_4d_parity_problem_5.csv & -python main.py -f=synthetic_cases/synthetic_4d_parity_problem_10.csv & - -python main.py -f=synthetic_cases/synthetic_5d_parity_problem_1.csv & -python main.py -f=synthetic_cases/synthetic_5d_parity_problem_2.csv & -python main.py -f=synthetic_cases/synthetic_5d_parity_problem_3.csv & -python main.py -f=synthetic_cases/synthetic_5d_parity_problem_4.csv & -python main.py -f=synthetic_cases/synthetic_5d_parity_problem_5.csv & -python main.py -f=synthetic_cases/synthetic_5d_parity_problem_10.csv & - -python main.py -f=synthetic_cases/synthetic_10d_parity_problem_1.csv & -python main.py -f=synthetic_cases/synthetic_10d_parity_problem_2.csv & -python main.py -f=synthetic_cases/synthetic_10d_parity_problem_3.csv & -python main.py -f=synthetic_cases/synthetic_10d_parity_problem_4.csv & -python main.py -f=synthetic_cases/synthetic_10d_parity_problem_5.csv & -python main.py -f=synthetic_cases/synthetic_10d_parity_problem_10.csv & - - -python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_1.csv & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_2.csv & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_3.csv & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_4.csv & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_5.csv & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_10.csv & - -python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_1.csv & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_2.csv & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_3.csv & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_4.csv & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_5.csv & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_10.csv & - -python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_1.csv & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_2.csv & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_3.csv & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_4.csv & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_5.csv & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_10.csv & - -python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_1.csv & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_2.csv & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_3.csv & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_4.csv & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_5.csv & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_10.csv & - -python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_1.csv & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_2.csv & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_3.csv & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_4.csv & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_5.csv & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_10.csv & +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_1.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_2.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_3.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_4.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_5.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_10.csv -m=HET_BEAM_SEARCH -cor=uds & + +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_1.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_2.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_3.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_4.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_5.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_10.csv -m=HET_BEAM_SEARCH -cor=uds & + +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_1.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_2.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_3.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_4.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_5.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_10.csv -m=HET_BEAM_SEARCH -cor=uds & + +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_1.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_2.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_3.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_4.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_5.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_10.csv -m=HET_BEAM_SEARCH -cor=uds & + +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_1.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_2.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_3.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_4.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_5.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_10.csv -m=HET_BEAM_SEARCH -cor=uds & + + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_1.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_2.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_3.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_4.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_5.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_10.csv -m=HET_BEAM_SEARCH -cor=uds & + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_1.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_2.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_3.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_4.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_5.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_10.csv -m=HET_BEAM_SEARCH -cor=uds & + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_1.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_2.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_3.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_4.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_5.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_10.csv -m=HET_BEAM_SEARCH -cor=uds & + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_1.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_2.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_3.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_4.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_5.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_10.csv -m=HET_BEAM_SEARCH -cor=uds & + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_1.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_2.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_3.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_4.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_5.csv -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_10.csv -m=HET_BEAM_SEARCH -cor=uds & # ----with added irrelevant features and proposed algorithms---- -python main.py -f=synthetic_cases/synthetic_2d_parity_problem_1.csv -m=greedy_topk -cor=uds & #todo add more commands # -------------CJS experiments------------- # ----original synthetic cases---- -python main.py -f=synthetic_cases/synthetic_2d_parity_problem.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_3d_parity_problem.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_4d_parity_problem.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_5d_parity_problem.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_10d_parity_problem.csv -dist=CJS & - -python main.py -f=synthetic_cases/synthetic_cube_in_cube_2.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_3.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_4.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_5.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_10.csv -dist=CJS & +python main.py -f=synthetic_cases/synthetic_2d_parity_problem.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & # ----with added irrelevant features---- -python main.py -f=synthetic_cases/synthetic_2d_parity_problem_1.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_2d_parity_problem_2.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_2d_parity_problem_3.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_2d_parity_problem_4.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_2d_parity_problem_5.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_2d_parity_problem_10.csv -dist=CJS & - -python main.py -f=synthetic_cases/synthetic_3d_parity_problem_1.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_3d_parity_problem_2.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_3d_parity_problem_3.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_3d_parity_problem_4.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_3d_parity_problem_5.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_3d_parity_problem_10.csv -dist=CJS & - -python main.py -f=synthetic_cases/synthetic_4d_parity_problem_1.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_4d_parity_problem_2.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_4d_parity_problem_3.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_4d_parity_problem_4.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_4d_parity_problem_5.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_4d_parity_problem_10.csv -dist=CJS & - -python main.py -f=synthetic_cases/synthetic_5d_parity_problem_1.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_5d_parity_problem_2.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_5d_parity_problem_3.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_5d_parity_problem_4.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_5d_parity_problem_5.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_5d_parity_problem_10.csv -dist=CJS & - -python main.py -f=synthetic_cases/synthetic_10d_parity_problem_1.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_10d_parity_problem_2.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_10d_parity_problem_3.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_10d_parity_problem_4.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_10d_parity_problem_5.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_10d_parity_problem_10.csv -dist=CJS & - - -python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_1.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_2.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_3.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_4.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_5.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_10.csv -dist=CJS & - -python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_1.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_2.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_3.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_4.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_5.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_10.csv -dist=CJS & - -python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_1.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_2.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_3.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_4.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_5.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_10.csv -dist=CJS & - -python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_1.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_2.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_3.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_4.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_5.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_10.csv -dist=CJS & - -python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_1.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_2.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_3.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_4.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_5.csv -dist=CJS & -python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_10.csv -dist=CJS & +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_1.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_2.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_3.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_4.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_5.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_2d_parity_problem_10.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & + +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_1.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_2.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_3.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_4.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_5.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_3d_parity_problem_10.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & + +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_1.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_2.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_3.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_4.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_5.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_4d_parity_problem_10.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & + +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_1.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_2.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_3.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_4.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_5.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_5d_parity_problem_10.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & + +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_1.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_2.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_3.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_4.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_5.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_10d_parity_problem_10.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & + + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_1.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_2.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_3.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_4.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_5.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_2_10.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_1.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_2.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_3.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_4.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_5.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_3_10.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_1.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_2.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_3.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_4.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_5.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_4_10.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_1.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_2.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_3.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_4.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_5.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_5_10.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & + +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_1.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_2.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_3.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_4.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_5.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & +python main.py -f=synthetic_cases/synthetic_cube_in_cube_10_10.csv -dist=CJS -m=HET_BEAM_SEARCH -cor=uds & wait \ No newline at end of file diff --git a/subspace_mining.py b/subspace_mining.py index dfdb996..09af626 100644 --- a/subspace_mining.py +++ b/subspace_mining.py @@ -1,7 +1,9 @@ import numpy as np +import pandas as pd from constants import CorrelationMeasure from uds import compute_uds +import constants as cst def compute_measure(data, cor_measure): @@ -22,7 +24,7 @@ def greedy_topk(data, curr, k, cor_measure): ''' dims = data.columns.tolist() dims.remove(curr) - if data.shape[1] <= k: + if data.shape[1] - 1 <= k: return dims corr = [] for dim in dims: @@ -33,11 +35,11 @@ def greedy_topk(data, curr, k, cor_measure): order.reverse() return [dims[o] for o in order[:k]] -# todo + def het_greedy_topk(data, curr, k, delta, cor_measure): dims = data.columns.tolist() dims.remove(curr) - if data.shape[1] <= k: + if data.shape[1] - 1 <= k: return dims corr = [] for dim in dims: @@ -47,17 +49,98 @@ def het_greedy_topk(data, curr, k, delta, cor_measure): order = np.argsort(corr).tolist() order.reverse() - # diverse_dims = [order[0]] - # for i, o in enumerate(order): - # for p in order[:i]: - # if p not in diverse_dims: - # continue - # if compute_measure(data.loc[:, [dims[o], dims[p]]], cor_measure) > delta: - # deleted.add(o) - # continue - # diverse_dims_counter += 1 - # if diverse_dims_counter == k: - # return [dims[l] for l in order ] - # het_dims = [] - # for o in order[:k] - return dims \ No newline at end of file + diverse_dims_id = [] + for i, o in enumerate(order): + delete_flag = False + for p in order[:i]: + if p not in diverse_dims_id: + continue + if compute_measure(data.loc[:, [dims[o], dims[p]]], cor_measure) > delta: + delete_flag = True + continue + if not delete_flag: + diverse_dims_id.append(o) + + if len(diverse_dims_id) == k: + return [dims[l] for l in diverse_dims_id] + return [dims[o] for o in diverse_dims_id] + + +class Score: + def __init__(self, subspace, score): + self.score = score + self.subspace = subspace + + def __lt__(self, other): + return self.score < other.score + + +def best_first(data, curr, k, cor_measure): + dims = set(data.columns.tolist()) + level = 1 + best = [Score({curr}, 0)] + while level <= k and level < len(dims): + corr = set() + for j in dims - best[level - 1].subspace: + s = best[level - 1].subspace.union({j}) + corr.add(Score(s, compute_measure(data.loc[:, s], cor_measure))) + best.append(sorted(corr, reverse=True)[0]) + level += 1 + + return sorted(best, reverse=True)[0].subspace - {curr} + + +def beam_search(data, curr, k, beam_width, cor_measure): + dims = set(data.columns.tolist()) + level = 1 + best = [[Score({curr}, 0)]] + while level <= k and level < len(dims): + corr = set() + for b in best[level - 1]: + for j in dims - b.subspace: + s = b.subspace.union({j}) + corr.add(Score(s, compute_measure(data.loc[:, s], cor_measure))) + best.append(sorted(corr, reverse=True)[:beam_width]) + level += 1 + + return sorted([a[0] for a in best], reverse=True)[0].subspace - {curr} + + +def het_beam_search(data, curr, k, beam_width, delta, cor_measure): + dims = set(data.columns.tolist()) + level = 1 + best = [[Score({curr}, 0)]] + while level <= k and level < len(dims): + corr = set() + for b in best[level - 1]: + for j in dims - b.subspace: + s = b.subspace.union({j}) + corr.add(Score(s, compute_measure(data.loc[:, s], cor_measure))) + + corr = sorted(corr, reverse=True) + + # checking if subspace of c does not correlate with the subspaces seen earlier + diverse_corr = [] + for i, c in enumerate(corr): + delete_flag = False + for corr_l in corr[:i]: + if corr_l not in diverse_corr: + continue + if compute_measure(data.loc[:, c.subspace.union(corr_l.subspace)], cor_measure) > delta: + delete_flag = True + continue + if not delete_flag: + diverse_corr.append(c) + if len(diverse_corr) == beam_width: + break + + best.append(diverse_corr) + level += 1 + + return sorted([a[0] for a in best], reverse=True)[0].subspace - {curr} + + +if __name__ == '__main__': + data = pd.read_csv('synthetic_cases/synthetic_with_nearcopies_4_3.csv', delimiter=';', header=None, na_values='?') + # data = data.loc[:, :data.shape[1] - 2] + print(str(beam_search(data, 4, 4, cst.BEAM_WIDTH, cst.CorrelationMeasure.UDS))) diff --git a/uds.py b/uds.py index bdda152..e314b1b 100644 --- a/uds.py +++ b/uds.py @@ -83,7 +83,7 @@ def compute_CE(data): curr_data = data.sort_values() data_diff = (curr_data[1:] - curr_data.shift(1)[1:]).reset_index(drop=True) CE = -math.log(pd.Series([((i + 1) / m) ** ((i + 1) * data_diff[i] / m) for i in range(len(data_diff))]).prod(), 2) - return CE + return CE if CE != 0 else float('inf') def entropy(I, N): @@ -116,7 +116,6 @@ def compute_uds(data): uds = 0 prev = perm[0] for dim in perm[1:]: - # todo should I pass binning? scores, discs = dim_optimal_disc(dim, prev, I, data) # regularization step