| Previous changeset 9:537c6763c018 (2018-07-13) Next changeset 11:9af844f24ef6 (2018-08-04) |
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Commit message:
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 76583c1fcd9d06a4679cc46ffaee44117b9e22cd |
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modified:
feature_selection.xml main_macros.xml test-data/feature_selection_result01 test-data/feature_selection_result08 test-data/feature_selection_result09 |
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added:
test-data/feature_selection_result12 test-data/pipeline01 test-data/pipeline02 test-data/pipeline03 test-data/pipeline04 test-data/pipeline05 test-data/pipeline06 test-data/pipeline07 test-data/pipeline08 test-data/searchCV01 |
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| diff -r 537c6763c018 -r 96f9b73327f2 feature_selection.xml --- a/feature_selection.xml Fri Jul 13 03:55:31 2018 -0400 +++ b/feature_selection.xml Sat Aug 04 12:35:10 2018 -0400 |
| [ |
| b'@@ -19,19 +19,28 @@\n import json\n import pandas\n import pickle\n+import ast\n import numpy as np\n+import xgboost\n import sklearn.feature_selection\n-from sklearn import svm, linear_model, ensemble\n+from sklearn import svm, linear_model, ensemble, naive_bayes, tree, neighbors\n \n @COLUMNS_FUNCTION@\n-\n+@GET_ESTIMATOR_FUNCTION@\n @FEATURE_SELECTOR_FUNCTION@\n \n input_json_path = sys.argv[1]\n with open(input_json_path, "r") as param_handler:\n params = json.load(param_handler)\n \n-## Read features\n+#handle cheetah\n+#if $fs_algorithm_selector.selected_algorithm == "SelectFromModel"\\\n+ and $fs_algorithm_selector.model_inputter.input_mode == "prefitted":\n+params[\'fs_algorithm_selector\'][\'model_inputter\'][\'fitted_estimator\'] =\\\n+ "$fs_algorithm_selector.model_inputter.fitted_estimator"\n+#end if\n+\n+# Read features\n features_has_header = params["input_options"]["header1"]\n input_type = params["input_options"]["selected_input"]\n if input_type=="tabular":\n@@ -53,7 +62,7 @@\n else:\n X = mmread("$input_options.infile1")\n \n-## Read labels\n+# Read labels\n header = \'infer\' if params["input_options"]["header2"] else None\n column_option = params["input_options"]["column_selector_options_2"]["selected_column_selector_option2"]\n if column_option in ["by_index_number", "all_but_by_index_number", "by_header_name", "all_but_by_header_name"]:\n@@ -70,21 +79,20 @@\n )\n y=y.ravel()\n \n-## Create feature selector\n-new_selector = feature_selector(params[\'feature_selection_algorithms\'])\n-if params[\'feature_selection_algorithms\'][\'selected_algorithm\'] != \'SelectFromModel\' or \\\n- \'extra_estimator\' not in params[\'feature_selection_algorithms\'] or \\\n- params[\'feature_selection_algorithms\'][\'extra_estimator\'][\'has_estimator\'] != \'no_load\' :\n+# Create feature selector\n+new_selector = feature_selector(params[\'fs_algorithm_selector\'])\n+if params[\'fs_algorithm_selector\'][\'selected_algorithm\'] != \'SelectFromModel\'\\\n+ or params[\'fs_algorithm_selector\'][\'model_inputter\'][\'input_mode\'] != \'prefitted\' :\n new_selector.fit(X, y)\n \n ## Transform to select features\n selected_names = None\n-if "$select_methods.selected_method" == "fit_transform":\n+if "$output_method_selector.selected_method" == "fit_transform":\n res = new_selector.transform(X)\n if features_has_header:\n selected_names = input_df.columns[new_selector.get_support(indices=True)]\n else:\n- res = new_selector.get_support(params["select_methods"]["indices"])\n+ res = new_selector.get_support(params["output_method_selector"]["indices"])\n \n res = pandas.DataFrame(res, columns = selected_names)\n res.to_csv(path_or_buf="$outfile", sep=\'\\t\', index=False)\n@@ -94,8 +102,10 @@\n </configfile>\n </configfiles>\n <inputs>\n- <expand macro="feature_selection_all" />\n- <expand macro="feature_selection_methods" />\n+ <expand macro="feature_selection_all">\n+ <expand macro="fs_selectfrommodel_prefitted"/>\n+ </expand>\n+ <expand macro="feature_selection_output_mothods" />\n <expand macro="sl_mixed_input"/>\n </inputs>\n <outputs>\n@@ -104,14 +114,16 @@\n <tests>\n <test>\n <param name="selected_algorithm" value="SelectFromModel"/>\n- <param name="has_estimator" value="no"/>\n- <param name="new_estimator" value="ensemble.RandomForestRegressor(n_estimators = 1000, random_state = 42)"/>\n- <param name="infile1" value="regression_X.tabular" ftype="tabular"/>\n- <param name="header1" value="True"/>\n- <param name="col1" value="1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17"/>\n- <param name="infile2" value="regression_y.tabular" ftype="tabular"/>\n- <param name="col2" value="1"/>\n- <param name="header2" value="True"/>\n+ <param name="input_mode" value="new"/>\n+ <param name="selected_module" value="ensemble"/>\n+ <param name="selected_estimator" value="RandomForestRegressor"/>\n+ '..b'5"/>\n+ <param name="infile2" value="regression_train.tabular" ftype="tabular"/>\n+ <param name="col2" value="6"/>\n+ <param name="header2" value="false"/>\n <output name="outfile" file="feature_selection_result01"/>\n </test>\n <test>\n@@ -180,26 +192,30 @@\n </test>\n <test>\n <param name="selected_algorithm" value="RFE"/>\n- <param name="has_estimator" value="no"/>\n- <param name="new_estimator" value="ensemble.RandomForestRegressor(n_estimators = 1000, random_state = 42)"/>\n- <param name="infile1" value="regression_X.tabular" ftype="tabular"/>\n- <param name="header1" value="True"/>\n- <param name="col1" value="1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17"/>\n- <param name="infile2" value="regression_y.tabular" ftype="tabular"/>\n- <param name="col2" value="1"/>\n- <param name="header2" value="True"/>\n+ <param name="input_mode" value="new"/>\n+ <param name="selected_module" value="ensemble"/>\n+ <param name="selected_estimator" value="RandomForestRegressor"/>\n+ <param name="text_params" value="\'n_estimators\': 10, \'random_state\':10"/>\n+ <param name="infile1" value="regression_train.tabular" ftype="tabular"/>\n+ <param name="header1" value="false"/>\n+ <param name="col1" value="1,2,3,4,5"/>\n+ <param name="infile2" value="regression_train.tabular" ftype="tabular"/>\n+ <param name="col2" value="6"/>\n+ <param name="header2" value="false"/>\n <output name="outfile" file="feature_selection_result08"/>\n </test>\n <test>\n <param name="selected_algorithm" value="RFECV"/>\n- <param name="has_estimator" value="no"/>\n- <param name="new_estimator" value="ensemble.RandomForestRegressor(n_estimators = 1000, random_state = 42)"/>\n- <param name="infile1" value="regression_X.tabular" ftype="tabular"/>\n- <param name="header1" value="True"/>\n- <param name="col1" value="1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17"/>\n- <param name="infile2" value="regression_y.tabular" ftype="tabular"/>\n- <param name="col2" value="1"/>\n- <param name="header2" value="True"/>\n+ <param name="input_mode" value="new"/>\n+ <param name="selected_module" value="ensemble"/>\n+ <param name="selected_estimator" value="RandomForestRegressor"/>\n+ <param name="text_params" value="\'n_estimators\': 10, \'random_state\':10"/>\n+ <param name="infile1" value="regression_train.tabular" ftype="tabular"/>\n+ <param name="header1" value="false"/>\n+ <param name="col1" value="1,2,3,4,5"/>\n+ <param name="infile2" value="regression_train.tabular" ftype="tabular"/>\n+ <param name="col2" value="6"/>\n+ <param name="header2" value="false"/>\n <output name="outfile" file="feature_selection_result09"/>\n </test>\n <test>\n@@ -226,6 +242,18 @@\n <param name="col2" value="target"/>\n <output name="outfile" file="feature_selection_result11"/>\n </test>\n+ <test>\n+ <param name="selected_algorithm" value="SelectFromModel"/>\n+ <param name="input_mode" value="prefitted"/>\n+ <param name="fitted_estimator" value="rfr_model01" ftype="zip"/>\n+ <param name="infile1" value="regression_train.tabular" ftype="tabular"/>\n+ <param name="header1" value="false"/>\n+ <param name="col1" value="1,2,3,4,5"/>\n+ <param name="infile2" value="regression_train.tabular" ftype="tabular"/>\n+ <param name="col2" value="1"/>\n+ <param name="header2" value="false"/>\n+ <output name="outfile" file="feature_selection_result12"/>\n+ </test>\n </tests>\n <help>\n <![CDATA[\n' |
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| diff -r 537c6763c018 -r 96f9b73327f2 main_macros.xml --- a/main_macros.xml Fri Jul 13 03:55:31 2018 -0400 +++ b/main_macros.xml Sat Aug 04 12:35:10 2018 -0400 |
| [ |
| b'@@ -34,24 +34,20 @@\n if inputs[\'selected_algorithm\'] == \'SelectFromModel\':\n if not options[\'threshold\'] or options[\'threshold\'] == \'None\':\n options[\'threshold\'] = None\n- if \'extra_estimator\' in inputs and inputs[\'extra_estimator\'][\'has_estimator\'] == \'no_load\':\n- with open("inputs[\'extra_estimator\'][\'fitted_estimator\']", \'rb\') as model_handler:\n- fitted_estimator = pickle.load(model_handler)\n- new_selector = selector(fitted_estimator, prefit=True, **options)\n- else:\n- estimator=inputs["estimator"]\n- if inputs["extra_estimator"]["has_estimator"]==\'no\':\n- estimator=inputs["extra_estimator"]["new_estimator"]\n- estimator=eval(estimator.replace(\'__dq__\', \'"\').replace("__sq__","\'"))\n- new_selector = selector(estimator, **options)\n+ if inputs[\'model_inputter\'][\'input_mode\'] == \'prefitted\':\n+ model_file = inputs[\'model_inputter\'][\'fitted_estimator\']\n+ with open(model_file, \'rb\') as model_handler:\n+ fitted_estimator = pickle.load(model_handler)\n+ new_selector = selector(fitted_estimator, prefit=True, **options)\n+ else:\n+ estimator_json = inputs[\'model_inputter\']["estimator_selector"]\n+ estimator = get_estimator(estimator_json)\n+ new_selector = selector(estimator, **options)\n \n elif inputs[\'selected_algorithm\'] in [\'RFE\', \'RFECV\']:\n if \'scoring\' in options and (not options[\'scoring\'] or options[\'scoring\'] == \'None\'):\n options[\'scoring\'] = None\n- estimator=inputs["estimator"]\n- if inputs["extra_estimator"]["has_estimator"]==\'no\':\n- estimator=inputs["extra_estimator"]["new_estimator"]\n- estimator=eval(estimator.replace(\'__dq__\', \'"\').replace("__sq__","\'"))\n+ estimator=get_estimator(inputs["estimator_selector"])\n new_selector = selector(estimator, **options)\n \n elif inputs[\'selected_algorithm\'] == "VarianceThreshold":\n@@ -104,11 +100,101 @@\n return X, y\n </token>\n \n+ <token name="@GET_SEARCH_PARAMS_FUNCTION@">\n+def get_search_params(params_builder):\n+ search_params = {}\n+\n+ def safe_eval(literal):\n+\n+ FROM_SCIPY_STATS = [ \'bernoulli\', \'binom\', \'boltzmann\', \'dlaplace\', \'geom\', \'hypergeom\',\n+ \'logser\', \'nbinom\', \'planck\', \'poisson\', \'randint\', \'skellam\', \'zipf\' ]\n+\n+ FROM_NUMPY_RANDOM = [ \'beta\', \'binomial\', \'bytes\', \'chisquare\', \'choice\', \'dirichlet\', \'division\',\n+ \'exponential\', \'f\', \'gamma\', \'geometric\', \'gumbel\', \'hypergeometric\',\n+ \'laplace\', \'logistic\', \'lognormal\', \'logseries\', \'mtrand\', \'multinomial\',\n+ \'multivariate_normal\', \'negative_binomial\', \'noncentral_chisquare\', \'noncentral_f\',\n+ \'normal\', \'pareto\', \'permutation\', \'poisson\', \'power\', \'rand\', \'randint\',\n+ \'randn\', \'random\', \'random_integers\', \'random_sample\', \'ranf\', \'rayleigh\',\n+ \'sample\', \'seed\', \'set_state\', \'shuffle\', \'standard_cauchy\', \'standard_exponential\',\n+ \'standard_gamma\', \'standard_normal\', \'standard_t\', \'triangular\', \'uniform\',\n+ \'vonmises\', \'wald\', \'weibull\', \'zipf\' ]\n+\n+ # File opening and other unneeded functions could be dropped\n+ UNWANTED = [\'open\', \'type\', \'dir\', \'id\', \'str\', \'repr\']\n+\n+ # Allowed symbol table. Add more if needed.\n+ new_syms = {\n+ \'np_arange\': getattr(np, \'arange\'),\n+ \'ensemble_ExtraTreesClassifier\': getattr(ensemble, \'ExtraTreesClassifier\')\n+ }\n+\n+ syms = make_symbol_table(use_numpy=False, **new_syms)\n+\n+ for method in FROM_SCIPY_STATS:\n+ syms[\'scipy_stats_\' + method] = getattr(scipy.stats, method)\n+\n+ for func in FROM_NUMPY_RANDOM:\n+ syms[\'np_random_\' + func] = getattr(np.random, func)\n+\n+ for key in UNWANTED:\n+ syms.pop(key, None)\n+\n+ aeval = Interpreter(symtable=syms, use_numpy=False, minimal=False,\n+ no_if=True, no_for=True, no_while=True, no_try=True,\n+ '..b'"Type in maxtrix decomposition parameters:"\n+ help="Parameters in dictionary without braces (\'{}\'), e.g., \'n_components\': 100, \'whiten\': False. No double quotes. Leave this box blank for class default."/>\n+ </when>\n+ <when value="KernelPCA">\n+ <expand macro="estimator_params_text" label="Type in maxtrix decomposition parameters:"\n+ help="Parameters in dictionary without braces (\'{}\'), e.g., \'n_components\': 100, \'random_state\': 42. No double quotes. Leave this box blank for class default."/>\n+ </when>\n+ <when value="LatentDirichletAllocation">\n+ <expand macro="estimator_params_text" label="Type in maxtrix decomposition parameters:"\n+ help="Parameters in dictionary without braces (\'{}\'), e.g., \'n_components\': 100, \'random_state\': 42. No double quotes. Leave this box blank for class default."/>\n+ </when>\n+ <when value="MiniBatchDictionaryLearning">\n+ <expand macro="estimator_params_text" label="Type in maxtrix decomposition parameters:"\n+ help="Parameters in dictionary without braces (\'{}\'), e.g., \'n_components\': 100, \'random_state\': 42. No double quotes. Leave this box blank for class default."/>\n+ </when>\n+ <when value="MiniBatchSparsePCA">\n+ <expand macro="estimator_params_text" label="Type in maxtrix decomposition parameters:"\n+ help="Parameters in dictionary without braces (\'{}\'), e.g., \'n_components\': 100, \'random_state\': 42. No double quotes. Leave this box blank for class default."/>\n+ </when>\n+ <when value="NMF">\n+ <expand macro="estimator_params_text" label="Type in maxtrix decomposition parameters:"\n+ help="Parameters in dictionary without braces (\'{}\'), e.g., \'n_components\': 100, \'init\': \'random\'. No double quotes. Leave this box blank for class default."/>\n+ </when>\n+ <when value="PCA">\n+ <expand macro="estimator_params_text" label="Type in maxtrix decomposition parameters:"\n+ help="Parameters in dictionary without braces (\'{}\'), e.g., \'n_components\': 100, \'random_state\': 42. No double quotes. Leave this box blank for class default."/>\n+ </when>\n+ <when value="SparsePCA">\n+ <expand macro="estimator_params_text" label="Type in maxtrix decomposition parameters:"\n+ help="Parameters in dictionary without braces (\'{}\'), e.g., \'n_components\': 100, \'random_state\': 42. No double quotes. Leave this box blank for class default."/>\n+ </when>\n+ <when value="SparseCoder">\n+ <expand macro="estimator_params_text" label="Type in maxtrix decomposition parameters:"\n+ help="Parameters in dictionary without braces (\'{}\'), e.g., \'transform_algorithm\': \'omp\', \'transform_alpha\': 1.0. No double quotes. Leave this box blank for class default."/>\n+ </when>\n+ <when value="TruncatedSVD">\n+ <expand macro="estimator_params_text" label="Type in maxtrix decomposition parameters:"\n+ help="Parameters in dictionary without braces (\'{}\'), e.g., \'n_components\': 2, \'algorithm\': \'randomized\'. No double quotes. Leave this box blank for default estimator."/>\n+ </when>\n+ </conditional>\n+ </xml>\n+\n+ <xml name="FeatureAgglomeration">\n+ <conditional name="FeatureAgglomeration_selector">\n+ <param name="select_algorithm" type="select" label="Choose the algorithm:">\n+ <option value="FeatureAgglomeration" selected="true">FeatureAgglomeration</option>\n+ </param>\n+ <when value="FeatureAgglomeration">\n+ <expand macro="estimator_params_text" label="Type in parameters:"\n+ help="Parameters in dictionary without braces (\'{}\'), e.g., \'n_clusters\': 2, \'affinity\': \'euclidean\'. No double quotes. Leave this box blank for class default."/>\n+ </when>\n+ </conditional>\n+ </xml>\n <!-- Outputs -->\n \n <xml name="output">\n@@ -1118,7 +1472,6 @@\n </outputs>\n </xml>\n \n-\n <!--Citations-->\n <xml name="eden_citation">\n <citations>\n' |
| b |
| diff -r 537c6763c018 -r 96f9b73327f2 test-data/feature_selection_result01 --- a/test-data/feature_selection_result01 Fri Jul 13 03:55:31 2018 -0400 +++ b/test-data/feature_selection_result01 Sat Aug 04 12:35:10 2018 -0400 |
| b |
| @@ -1,262 +1,11 @@ -temp_1 average -69.0 69.7 -59.0 58.1 -88.0 77.3 -65.0 64.7 -50.0 47.5 -51.0 48.2 -52.0 48.6 -78.0 76.7 -35.0 45.2 -40.0 46.1 -47.0 45.3 -72.0 76.3 -76.0 74.4 -39.0 45.3 -78.0 72.2 -71.0 67.3 -48.0 47.7 -72.0 77.0 -57.0 54.7 -40.0 45.1 -54.0 47.6 -58.0 53.2 -68.0 58.6 -65.0 55.3 -47.0 48.8 -44.0 45.6 -64.0 67.1 -62.0 57.1 -66.0 65.7 -70.0 71.8 -57.0 54.2 -50.0 50.5 -55.0 51.8 -55.0 49.5 -42.0 45.2 -65.0 60.1 -63.0 65.6 -48.0 47.3 -42.0 46.3 -51.0 46.2 -64.0 68.0 -75.0 74.6 -52.0 46.7 -67.0 68.6 -68.0 68.7 -54.0 55.0 -62.0 56.8 -76.0 76.1 -73.0 73.1 -52.0 50.3 -70.0 73.9 -77.0 77.4 -60.0 56.6 -52.0 53.3 -79.0 75.0 -76.0 57.2 -66.0 66.5 -57.0 61.8 -66.0 57.4 -61.0 58.4 -55.0 53.1 -48.0 48.1 -49.0 49.2 -65.0 66.7 -60.0 62.5 -56.0 53.0 -59.0 57.4 -44.0 45.7 -82.0 63.2 -64.0 67.0 -43.0 45.5 -64.0 55.7 -63.0 52.7 -70.0 70.6 -71.0 52.4 -76.0 73.5 -68.0 62.1 -39.0 45.3 -71.0 70.7 -69.0 71.7 -74.0 71.5 -81.0 64.1 -51.0 49.3 -45.0 46.8 -87.0 76.8 -71.0 73.8 -55.0 60.3 -80.0 76.9 -67.0 69.0 -61.0 61.4 -46.0 46.6 -39.0 45.1 -67.0 68.3 -52.0 47.8 -67.0 69.8 -75.0 71.2 -68.0 73.3 -92.0 68.2 -67.0 72.8 -44.0 45.8 -61.0 61.0 -65.0 53.4 -68.0 73.0 -87.0 62.1 -117.0 54.8 -80.0 76.4 -57.0 51.0 -67.0 63.6 -58.0 54.0 -65.0 56.2 -52.0 48.6 -59.0 55.3 -57.0 53.9 -81.0 59.2 -75.0 77.1 -76.0 77.4 -57.0 64.8 -69.0 74.2 -77.0 66.8 -55.0 49.9 -49.0 46.8 -54.0 52.7 -55.0 51.2 -56.0 55.6 -68.0 74.6 -54.0 53.4 -67.0 69.0 -49.0 46.9 -49.0 49.1 -56.0 48.5 -73.0 71.0 -66.0 66.4 -69.0 66.5 -82.0 64.5 -90.0 76.7 -51.0 50.7 -77.0 57.1 -60.0 61.4 -74.0 72.8 -85.0 77.2 -68.0 62.8 -56.0 49.5 -71.0 56.2 -62.0 59.5 -83.0 77.3 -64.0 65.4 -56.0 48.4 -41.0 45.1 -65.0 66.2 -65.0 53.7 -40.0 46.0 -45.0 45.6 -52.0 48.4 -63.0 51.7 -52.0 47.6 -60.0 57.9 -81.0 75.7 -75.0 75.8 -59.0 51.4 -73.0 77.1 -75.0 77.3 -60.0 58.5 -75.0 71.3 -59.0 57.6 -53.0 49.1 -79.0 77.2 -57.0 52.1 -75.0 67.6 -71.0 69.4 -53.0 50.2 -46.0 48.8 -81.0 76.9 -49.0 48.9 -57.0 48.4 -60.0 58.8 -67.0 73.7 -61.0 64.1 -66.0 69.5 -64.0 51.9 -66.0 65.7 -64.0 52.2 -71.0 65.2 -75.0 63.8 -48.0 46.4 -53.0 52.5 -49.0 47.1 -85.0 68.5 -62.0 49.4 -50.0 47.0 -58.0 55.9 -72.0 77.2 -55.0 50.7 -74.0 72.3 -85.0 77.3 -73.0 77.3 -52.0 47.4 -67.0 67.6 -45.0 45.1 -46.0 47.2 -66.0 60.6 -71.0 77.0 -70.0 69.3 -58.0 49.9 -72.0 77.1 -74.0 75.4 -65.0 64.5 -77.0 58.8 -59.0 50.9 -45.0 45.7 -53.0 50.5 -53.0 54.9 -79.0 77.3 -49.0 49.0 -63.0 62.9 -69.0 56.5 -60.0 50.8 -64.0 62.5 -79.0 71.0 -55.0 47.0 -73.0 56.0 -60.0 59.1 -67.0 70.2 -42.0 45.2 -60.0 65.0 -57.0 49.8 -35.0 45.2 -75.0 70.3 -61.0 51.1 -51.0 50.6 -71.0 71.9 -74.0 75.3 -48.0 45.4 -74.0 74.9 -76.0 70.8 -58.0 51.6 -51.0 50.4 -72.0 72.6 -76.0 67.2 -52.0 47.9 -53.0 48.2 -65.0 69.1 -58.0 58.1 -77.0 75.6 -61.0 52.9 -67.0 65.3 -54.0 49.3 -79.0 67.4 -77.0 64.3 -71.0 67.7 -58.0 57.7 -68.0 55.9 -40.0 45.4 -80.0 77.3 -74.0 62.3 -57.0 45.5 -52.0 47.8 -71.0 75.1 -49.0 53.6 -89.0 59.0 -60.0 60.2 -59.0 58.3 +0 1 +143.762620712 -1.1796457192799998 +-88.5787166225 -2.5710918402200003 +-82.8452345578 -0.168636324107 +72.4951388149 0.991068834926 +11.805182128 -0.7096855607860001 +-63.9354970901 0.9841122108220001 +126.32584079600001 0.35353444883900004 +23.0341392692 1.03188231893 +67.6714937696 -0.8214378651719999 +47.39275848810001 -0.0942409319417 |
| b |
| diff -r 537c6763c018 -r 96f9b73327f2 test-data/feature_selection_result08 --- a/test-data/feature_selection_result08 Fri Jul 13 03:55:31 2018 -0400 +++ b/test-data/feature_selection_result08 Sat Aug 04 12:35:10 2018 -0400 |
| b |
| b'@@ -1,262 +1,11 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|
| b |
| diff -r 537c6763c018 -r 96f9b73327f2 test-data/feature_selection_result09 --- a/test-data/feature_selection_result09 Fri Jul 13 03:55:31 2018 -0400 +++ b/test-data/feature_selection_result09 Sat Aug 04 12:35:10 2018 -0400 |
| b |
| b'@@ -1,262 +1,11 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