10591722 31244 Sharath Kumar Reddy Alijarla 3 Supervised Classification 18983 sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),variancethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,decisiontreeclassifier=sklearn.tree.tree.DecisionTreeClassifier)(2) 8304495 Python_3.7.3. Sklearn_0.20.0. NumPy_1.21.5. SciPy_1.7.3. n_jobs null 18952 remainder "passthrough" 18952 sparse_threshold 0.3 18952 transformer_weights null 18952 transformers [{"oml-python:serialized_object": "component_reference", "value": {"key": "numeric", "step_name": "numeric", "argument_1": []}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "nominal", "step_name": "nominal", "argument_1": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35]}}] 18952 memory null 18953 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "imputer", "step_name": "imputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}] 18953 axis 0 18954 copy true 18954 missing_values "NaN" 18954 strategy "mean" 18954 verbose 0 18954 copy true 18955 with_mean true 18955 with_std true 18955 memory null 18956 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder"}}] 18956 copy true 18957 fill_value -1 18957 missing_values NaN 18957 strategy "constant" 18957 verbose 0 18957 categorical_features null 18958 categories null 18958 dtype {"oml-python:serialized_object": "type", "value": "np.float64"} 18958 handle_unknown "ignore" 18958 n_values null 18958 sparse true 18958 threshold 0.0 18959 class_weight null 18971 criterion "gini" 18971 max_depth null 18971 max_features 1.0 18971 max_leaf_nodes null 18971 min_impurity_decrease 0.0 18971 min_impurity_split null 18971 min_samples_leaf 7 18971 min_samples_split 13 18971 min_weight_fraction_leaf 0.0 18971 presort false 18971 random_state 0 18971 splitter "best" 18971 memory null 18983 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "columntransformer", "step_name": "columntransformer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "variancethreshold", "step_name": "variancethreshold"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "decisiontreeclassifier", "step_name": "decisiontreeclassifier"}}] 18983 openml-python Sklearn_0.20.0. 3 kr-vs-kp https://www.openml.org/data/download/3/dataset_3_kr-vs-kp.arff -1 22111577 description https://api.openml.org/data/download/22111577/description.xml -1 22111578 predictions https://api.openml.org/data/download/22111578/predictions.arff area_under_roc_curve 0.9981644558129423 [0.998164,0.998164] average_cost 0 f_measure 0.9806002028555738 [0.981437,0.979685] kappa 0.9611225931665138 kb_relative_information_score 0.9562742811615276 mean_absolute_error 0.022228701714778063 mean_prior_absolute_error 0.49901358092237413 weighted_recall 0.9806007509386734 [0.982025,0.979044] number_of_instances 3196 [1669,1527] precision 0.9806004243293541 [0.98085,0.980328] predictive_accuracy 0.9806007509386734 prior_entropy 0.998575539213492 relative_absolute_error 0.04454528406559727 root_mean_prior_squared_error 0.49950623821173523 root_mean_squared_error 0.11129743810718898 root_relative_squared_error 0.22281491119238275 total_cost 0 unweighted_recall 0.9805345208260499 [0.982025,0.979044] area_under_roc_curve 0.9964384955579038 [0.996438,0.996438] area_under_roc_curve 0.9984540722476616 [0.998454,0.998454] area_under_roc_curve 0.9956948847403233 [0.995695,0.995695] area_under_roc_curve 0.9997847442370162 [0.999785,0.999785] area_under_roc_curve 0.9999608625885484 [0.999961,0.999961] area_under_roc_curve 0.9999608625885484 [0.999961,0.999961] area_under_roc_curve 0.9992912827781715 [0.999291,0.999291] area_under_roc_curve 0.9942286479672233 [0.994229,0.994229] area_under_roc_curve 0.9989560352978255 [0.998956,0.998956] area_under_roc_curve 0.9994090765836747 [0.999409,0.999409] average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 f_measure 0.9874960839598999 [0.988095,0.986842] f_measure 0.9687573345329369 [0.96988,0.967532] f_measure 0.9749921679197996 [0.97619,0.973684] f_measure 0.9843671959925964 [0.985163,0.983498] f_measure 0.9874911830400878 [0.988166,0.986755] f_measure 0.9968745412282848 [0.997015,0.996721] f_measure 0.9811978818544379 [0.981707,0.980645] f_measure 0.9686600603656251 [0.96988,0.96732] f_measure 0.9749216300940439 [0.976048,0.973684] f_measure 0.9811960362193749 [0.981928,0.980392] kappa 0.9749383247836474 kappa 0.9374144337962057 kappa 0.9498766495672945 kappa 0.9686643164904034 kappa 0.9749245778317597 kappa 0.9937362981522079 kappa 0.9623584015103839 kappa 0.9372022520571675 kappa 0.9497321147179325 kappa 0.9623213512343006 kb_relative_information_score 0.9686351760221783 kb_relative_information_score 0.9386213276067827 kb_relative_information_score 0.9511012536173221 kb_relative_information_score 0.9638056061267296 kb_relative_information_score 0.9696234066158036 kb_relative_information_score 0.976244516417505 kb_relative_information_score 0.9577614769904791 kb_relative_information_score 0.9206177891885352 kb_relative_information_score 0.952207620896192 kb_relative_information_score 0.9640223836670241 mean_absolute_error 0.01599702380952381 mean_absolute_error 0.030372908341658338 mean_absolute_error 0.02478670634920635 mean_absolute_error 0.018845217282717285 mean_absolute_error 0.015941220238095237 mean_absolute_error 0.012875124007936509 mean_absolute_error 0.021195627778699877 mean_absolute_error 0.040711108814557084 mean_absolute_error 0.02351832249951372 mean_absolute_error 0.01808938188248533 mean_prior_absolute_error 0.4990286898061312 mean_prior_absolute_error 0.4990286898061312 mean_prior_absolute_error 0.4990286898061312 mean_prior_absolute_error 0.4990286898061312 mean_prior_absolute_error 0.4990286898061312 mean_prior_absolute_error 0.4990286898061312 mean_prior_absolute_error 0.49909524173611874 mean_prior_absolute_error 0.4989560481570598 mean_prior_absolute_error 0.4989560481570598 mean_prior_absolute_error 0.4989560481570598 number_of_instances 320 [167,153] number_of_instances 320 [167,153] number_of_instances 320 [167,153] number_of_instances 320 [167,153] number_of_instances 320 [167,153] number_of_instances 320 [167,153] number_of_instances 319 [166,153] number_of_instances 319 [167,152] number_of_instances 319 [167,152] number_of_instances 319 [167,152] precision 0.9875695560170854 [0.982249,0.993377] precision 0.9688404203323557 [0.975758,0.96129] precision 0.975060739057173 [0.970414,0.980132] precision 0.984533088235294 [0.976471,0.993333] precision 0.9877923976608187 [0.976608,1] precision 0.9968936011904763 [0.994048,1] precision 0.9815131572946932 [0.993827,0.968153] precision 0.9687443173336591 [0.975758,0.961039] precision 0.9749216300940439 [0.976048,0.973684] precision 0.9812780740680426 [0.987879,0.974026] predictive_accuracy 0.9875 predictive_accuracy 0.96875 predictive_accuracy 0.975 predictive_accuracy 0.984375 predictive_accuracy 0.9875 predictive_accuracy 0.996875 predictive_accuracy 0.9811912225705329 predictive_accuracy 0.9686520376175548 predictive_accuracy 0.974921630094044 predictive_accuracy 0.9811912225705329 prior_entropy 0.9986191629215038 prior_entropy 0.9986191629215038 prior_entropy 0.9986191629215038 prior_entropy 0.9986191629215038 prior_entropy 0.9986191629215038 prior_entropy 0.9986191629215038 prior_entropy 0.9988113175509788 prior_entropy 0.9984094255154751 prior_entropy 0.9984094255154751 prior_entropy 0.9984094255154751 relative_absolute_error 0.03205632088154798 relative_absolute_error 0.06086405243245229 relative_absolute_error 0.049669902463595414 relative_absolute_error 0.037763795284071755 relative_absolute_error 0.03194449650637978 relative_absolute_error 0.025800368337416425 relative_absolute_error 0.042468102290396936 relative_absolute_error 0.08159257506733773 relative_absolute_error 0.04713505846132302 relative_absolute_error 0.03625445958476729 root_mean_prior_squared_error 0.4995213618016774 root_mean_prior_squared_error 0.4995213618016774 root_mean_prior_squared_error 0.4995213618016774 root_mean_prior_squared_error 0.4995213618016774 root_mean_prior_squared_error 0.4995213618016774 root_mean_prior_squared_error 0.4995213618016774 root_mean_prior_squared_error 0.4995879730599906 root_mean_prior_squared_error 0.49944864525507615 root_mean_prior_squared_error 0.49944864525507615 root_mean_prior_squared_error 0.49944864525507615 root_mean_squared_error 0.09917794732328741 root_mean_squared_error 0.13956941134754106 root_mean_squared_error 0.12048232699723928 root_mean_squared_error 0.09348714221954435 root_mean_squared_error 0.08320634989239081 root_mean_squared_error 0.07030471353263473 root_mean_squared_error 0.108595070287216 root_mean_squared_error 0.14986162657010654 root_mean_squared_error 0.12597096085665507 root_mean_squared_error 0.09666609069894903 root_relative_squared_error 0.1985459580058231 root_relative_squared_error 0.27940629174324205 root_relative_squared_error 0.2411955447964882 root_relative_squared_error 0.18715344201167738 root_relative_squared_error 0.1665721553774628 root_relative_squared_error 0.140744158125809 root_relative_squared_error 0.21736926456028974 root_relative_squared_error 0.30005412567205964 root_relative_squared_error 0.2522200471528354 root_relative_squared_error 0.19354560597432427 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 unweighted_recall 0.9872020664553246 [0.994012,0.980392] unweighted_recall 0.968964032718876 [0.964072,0.973856] unweighted_recall 0.9746780947908105 [0.982036,0.96732] unweighted_recall 0.9839340925991155 [0.994012,0.973856] unweighted_recall 0.9869281045751634 [1,0.973856] unweighted_recall 0.9967320261437909 [1,0.993464] unweighted_recall 0.9816717851799355 [0.96988,0.993464] unweighted_recall 0.9688780334068705 [0.964072,0.973684] unweighted_recall 0.9748660573589663 [0.976048,0.973684] unweighted_recall 0.9814450047273873 [0.976048,0.986842] usercpu_time_millis 93.75 usercpu_time_millis 62.5 usercpu_time_millis 62.5 usercpu_time_millis 46.875 usercpu_time_millis 62.5 usercpu_time_millis 62.5 usercpu_time_millis 62.5 usercpu_time_millis 46.875 usercpu_time_millis 78.125 usercpu_time_millis 46.875 usercpu_time_millis_testing 15.625 usercpu_time_millis_testing 0 usercpu_time_millis_testing 15.625 usercpu_time_millis_testing 0 usercpu_time_millis_testing 0 usercpu_time_millis_testing 0 usercpu_time_millis_testing 0 usercpu_time_millis_testing 0 usercpu_time_millis_testing 15.625 usercpu_time_millis_testing 15.625 usercpu_time_millis_training 78.125 usercpu_time_millis_training 62.5 usercpu_time_millis_training 46.875 usercpu_time_millis_training 46.875 usercpu_time_millis_training 62.5 usercpu_time_millis_training 62.5 usercpu_time_millis_training 62.5 usercpu_time_millis_training 46.875 usercpu_time_millis_training 62.5 usercpu_time_millis_training 31.25 wall_clock_time_millis 281.2793254852295 wall_clock_time_millis 62.47353553771973 wall_clock_time_millis 62.506675720214844 wall_clock_time_millis 53.43508720397949 wall_clock_time_millis 62.506675720214844 wall_clock_time_millis 62.505483627319336 wall_clock_time_millis 62.51072883605957 wall_clock_time_millis 62.50429153442383 wall_clock_time_millis 78.13167572021484 wall_clock_time_millis 62.50739097595215 wall_clock_time_millis_testing 15.625715255737305 wall_clock_time_millis_testing 0 wall_clock_time_millis_testing 15.62643051147461 wall_clock_time_millis_testing 0 wall_clock_time_millis_testing 0 wall_clock_time_millis_testing 0 wall_clock_time_millis_testing 0 wall_clock_time_millis_testing 0 wall_clock_time_millis_testing 15.625953674316406 wall_clock_time_millis_testing 15.622854232788086 wall_clock_time_millis_training 265.6536102294922 wall_clock_time_millis_training 62.47353553771973 wall_clock_time_millis_training 46.880245208740234 wall_clock_time_millis_training 53.43508720397949 wall_clock_time_millis_training 62.506675720214844 wall_clock_time_millis_training 62.505483627319336 wall_clock_time_millis_training 62.51072883605957 wall_clock_time_millis_training 62.50429153442383 wall_clock_time_millis_training 62.50572204589844 wall_clock_time_millis_training 46.88453674316406 weighted_recall 0.9875 [0.994012,0.980392] weighted_recall 0.96875 [0.964072,0.973856] weighted_recall 0.975 [0.982036,0.96732] weighted_recall 0.984375 [0.994012,0.973856] weighted_recall 0.9875 [1,0.973856] weighted_recall 0.996875 [1,0.993464] weighted_recall 0.9811912225705329 [0.96988,0.993464] weighted_recall 0.9686520376175548 [0.964072,0.973684] weighted_recall 0.9749216300940439 [0.976048,0.973684] weighted_recall 0.9811912225705329 [0.976048,0.986842]