10560712
6691
Sergey Redyuk
9985
Supervised Classification
18978
sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(missingindicator=sklearn.impute.MissingIndicator,imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),sgdclassifier=sklearn.linear_model.stochastic_gradient.SGDClassifier)(2)
8277062
Python_3.6.14. Sklearn_0.20.0. NumPy_1.19.5. SciPy_1.5.4.
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
n_jobs
null
18962
remainder
"passthrough"
18962
sparse_threshold
0.3
18962
transformer_weights
null
18962
transformers
[{"oml-python:serialized_object": "component_reference", "value": {"key": "numeric", "step_name": "numeric", "argument_1": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "nominal", "step_name": "nominal", "argument_1": []}}]
18962
memory
null
18963
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "missingindicator", "step_name": "missingindicator"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "imputer", "step_name": "imputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}]
18963
error_on_new
false
18964
features
"missing-only"
18964
missing_values
NaN
18964
sparse
"auto"
18964
memory
null
18978
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "columntransformer", "step_name": "columntransformer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "sgdclassifier", "step_name": "sgdclassifier"}}]
18978
alpha
3.8875083608209314e-05
18979
average
true
18979
class_weight
null
18979
early_stopping
false
18979
epsilon
0.1
18979
eta0
0.0
18979
fit_intercept
true
18979
l1_ratio
0.15
18979
learning_rate
"optimal"
18979
loss
"hinge"
18979
max_iter
null
18979
n_iter
null
18979
n_iter_no_change
5
18979
n_jobs
null
18979
penalty
"l2"
18979
power_t
0.5
18979
random_state
36822
18979
shuffle
true
18979
tol
4.896672457206874e-05
18979
validation_fraction
0.1
18979
verbose
0
18979
warm_start
false
18979
openml-python
Sklearn_0.20.0.
1475
first-order-theorem-proving
https://www.openml.org/data/download/1587932/phpPbCMyg
-1
22047522
description
https://api.openml.org/data/download/22047522/description.xml
-1
22047523
predictions
https://api.openml.org/data/download/22047523/predictions.arff
area_under_roc_curve
0.6091335514437342 [0.581043,0.527679,0.563471,0.593554,0.581152,0.660585]
average_cost
0
f_measure
0.41793967370100915 [0.304,0.115625,0.229167,0.287785,0.247604,0.652396]
kappa
0.2202283036757331
kb_relative_information_score
0.27982698227901054
mean_absolute_error
0.1785986705895223
mean_prior_absolute_error
0.2507645736611627
weighted_recall
0.4642039882314482 [0.261708,0.076132,0.161765,0.225284,0.248397,0.823414]
number_of_instances
6118 [1089,486,748,617,624,2554]
precision
0.4225095621402409 [0.362595,0.24026,0.392857,0.398281,0.246815,0.5402]
predictive_accuracy
0.46420398823144815
prior_entropy
2.3000072984859514
relative_absolute_error
0.7122165144062486
root_mean_prior_squared_error
0.35407492669342416
root_mean_squared_error
0.4226093593255151
root_relative_squared_error
1.1935591239744334
total_cost
0
unweighted_recall
0.2994499501044674 [0.261708,0.076132,0.161765,0.225284,0.248397,0.823414]
area_under_roc_curve
0.6156906005859057 [0.558785,0.533466,0.540365,0.607214,0.625423,0.676769]
area_under_roc_curve
0.5904631939924784 [0.577206,0.51906,0.549758,0.601085,0.552693,0.628291]
area_under_roc_curve
0.6091112461486498 [0.571429,0.543463,0.538436,0.603578,0.567786,0.670028]
area_under_roc_curve
0.585593058473008 [0.550377,0.564759,0.553929,0.548152,0.560645,0.629132]
area_under_roc_curve
0.6175779745788997 [0.587986,0.514191,0.595493,0.601994,0.63434,0.656303]
area_under_roc_curve
0.6132226576844935 [0.598464,0.499547,0.586034,0.595513,0.555191,0.667787]
area_under_roc_curve
0.6087126925525684 [0.564521,0.540363,0.533631,0.612551,0.562551,0.673109]
area_under_roc_curve
0.6113491696701677 [0.575684,0.519067,0.590056,0.593883,0.565748,0.665643]
area_under_roc_curve
0.6426637748762304 [0.64847,0.505976,0.579478,0.581088,0.573741,0.715697]
area_under_roc_curve
0.5970503013128088 [0.577251,0.536338,0.567354,0.590194,0.613023,0.623151]
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
0.41854771305862853 [0.256983,0.135135,0.171429,0.313725,0.316547,0.6624]
f_measure
0.39727251249305084 [0.303318,0.076923,0.189474,0.314607,0.196429,0.628571]
f_measure
0.40867764994702904 [0.27907,0.16,0.161616,0.301887,0.222222,0.656051]
f_measure
0.38824376008115763 [0.230303,0.210526,0.208696,0.181818,0.212766,0.635569]
f_measure
0.4285633808590218 [0.322581,0.068966,0.31068,0.318182,0.310559,0.633166]
f_measure
0.4237627142774257 [0.336957,0.032258,0.285714,0.285714,0.2,0.664671]
f_measure
0.40521174416766714 [0.259259,0.151515,0.145833,0.320755,0.21118,0.660348]
f_measure
0.42156324934067113 [0.283951,0.092308,0.290598,0.285714,0.220339,0.662651]
f_measure
0.45296884469696475 [0.419214,0.037037,0.267857,0.26087,0.235294,0.698052]
f_measure
0.4170856626041455 [0.298969,0.137931,0.238532,0.282609,0.326923,0.625564]
kappa
0.22809967894817307
kappa
0.18779192070453168
kappa
0.21398101004541079
kappa
0.1770517445015482
kappa
0.23635829020134125
kappa
0.23120741077248222
kappa
0.21244872713067256
kappa
0.22615606936416185
kappa
0.2797725670568929
kappa
0.20655022874571102
kb_relative_information_score
0.28152511466581565
kb_relative_information_score
0.262325582860823
kb_relative_information_score
0.2677085395495373
kb_relative_information_score
0.25545654135162815
kb_relative_information_score
0.2894905333511224
kb_relative_information_score
0.2901895380980285
kb_relative_information_score
0.2661519644558155
kb_relative_information_score
0.28632899672517587
kb_relative_information_score
0.31685627199019434
kb_relative_information_score
0.282411009428461
mean_absolute_error
0.1797385620915025
mean_absolute_error
0.1824618736383434
mean_absolute_error
0.18300653594771157
mean_absolute_error
0.18355119825707977
mean_absolute_error
0.18028322440087066
mean_absolute_error
0.17320261437908427
mean_absolute_error
0.18300653594771157
mean_absolute_error
0.175381263616557
mean_absolute_error
0.1669394435351876
mean_absolute_error
0.17839607201309252
mean_prior_absolute_error
0.25067495791407446
mean_prior_absolute_error
0.25083558171073006
mean_prior_absolute_error
0.25088921191526126
mean_prior_absolute_error
0.25084785528987646
mean_prior_absolute_error
0.25084785528987646
mean_prior_absolute_error
0.25084785528987646
mean_prior_absolute_error
0.25084785528987646
mean_prior_absolute_error
0.25067558048692967
mean_prior_absolute_error
0.25058368192114683
mean_prior_absolute_error
0.25059472840439195
number_of_instances
612 [109,48,74,62,63,256]
number_of_instances
612 [109,48,75,62,63,255]
number_of_instances
612 [108,49,75,62,63,255]
number_of_instances
612 [109,49,75,62,62,255]
number_of_instances
612 [109,49,75,62,62,255]
number_of_instances
612 [109,49,75,62,62,255]
number_of_instances
612 [109,49,75,62,62,255]
number_of_instances
612 [109,49,75,61,62,256]
number_of_instances
611 [109,48,75,61,62,256]
number_of_instances
611 [109,48,74,61,63,256]
precision
0.4136854969209494 [0.328571,0.192308,0.290323,0.4,0.289474,0.560976]
precision
0.438275961765403 [0.313725,0.5,0.45,0.518519,0.22449,0.509756]
precision
0.4127919779302316 [0.375,0.230769,0.333333,0.363636,0.197531,0.552279]
precision
0.39449624637590003 [0.339286,0.296296,0.3,0.307692,0.3125,0.5058]
precision
0.45593519524978077 [0.324074,0.222222,0.571429,0.538462,0.252525,0.552632]
precision
0.42702038965795425 [0.413333,0.076923,0.5,0.348837,0.263158,0.53753]
precision
0.42188483258862575 [0.396226,0.294118,0.333333,0.386364,0.171717,0.55291]
precision
0.42869229339837983 [0.433962,0.1875,0.404762,0.378378,0.232143,0.539216]
precision
0.4480118947553835 [0.4,0.166667,0.405405,0.387097,0.245614,0.597222]
precision
0.43497095745841113 [0.341176,0.4,0.371429,0.419355,0.414634,0.508557]
predictive_accuracy
0.46078431372549017
predictive_accuracy
0.4526143790849673
predictive_accuracy
0.45098039215686275
predictive_accuracy
0.4493464052287582
predictive_accuracy
0.4591503267973856
predictive_accuracy
0.4803921568627451
predictive_accuracy
0.45098039215686275
predictive_accuracy
0.47385620915032683
predictive_accuracy
0.49918166939443537
predictive_accuracy
0.4648117839607201
prior_entropy
2.2982053906988225
prior_entropy
2.3010980143383097
prior_entropy
2.3029972536480843
prior_entropy
2.301686142471426
prior_entropy
2.301686142471426
prior_entropy
2.301686142471426
prior_entropy
2.301686142471426
prior_entropy
2.2983403180467192
prior_entropy
2.2961240491639523
prior_entropy
2.2965513970017746
relative_absolute_error
0.717018419339329
relative_absolute_error
0.7274162317559997
relative_absolute_error
0.7294316664740559
relative_absolute_error
0.7317232114461192
relative_absolute_error
0.7186954984826869
relative_absolute_error
0.690468787061917
relative_absolute_error
0.7295519259522137
relative_absolute_error
0.6996344170257199
relative_absolute_error
0.66620237301693
relative_absolute_error
0.7118907614257936
root_mean_prior_squared_error
0.35394835494159665
root_mean_prior_squared_error
0.3541751851309153
root_mean_prior_squared_error
0.3542508884492025
root_mean_prior_squared_error
0.3541925116962025
root_mean_prior_squared_error
0.3541925116962025
root_mean_prior_squared_error
0.3541925116962025
root_mean_prior_squared_error
0.3541925116962025
root_mean_prior_squared_error
0.3539492344090008
root_mean_prior_squared_error
0.3538193917423618
root_mean_prior_squared_error
0.35383500173976573
root_mean_squared_error
0.423955849224306
root_mean_squared_error
0.42715556140397304
root_mean_squared_error
0.42779263194649764
root_mean_squared_error
0.4284287551706582
root_mean_squared_error
0.4245977206731928
root_mean_squared_error
0.4161761818978643
root_mean_squared_error
0.42779263194649764
root_mean_squared_error
0.41878546251816934
root_mean_squared_error
0.4085822359515739
root_mean_squared_error
0.42236959172399297
root_relative_squared_error
1.1977901388869598
root_relative_squared_error
1.2060572827711848
root_relative_squared_error
1.2075979084180635
root_relative_squared_error
1.2095929219930246
root_relative_squared_error
1.198776672719095
root_relative_squared_error
1.174999945382319
root_relative_squared_error
1.2077969404204212
root_relative_squared_error
1.1831794557132678
root_relative_squared_error
1.154776265765242
root_relative_squared_error
1.1936908153440178
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
0.308777012989266 [0.211009,0.104167,0.121622,0.258065,0.349206,0.808594]
unweighted_recall
0.2792103529452293 [0.293578,0.041667,0.12,0.225806,0.174603,0.819608]
unweighted_recall
0.2952022959721523 [0.222222,0.122449,0.106667,0.258065,0.253968,0.807843]
unweighted_recall
0.27380029569290476 [0.174312,0.163265,0.16,0.129032,0.16129,0.854902]
unweighted_recall
0.32424321765798164 [0.321101,0.040816,0.213333,0.225806,0.403226,0.741176]
unweighted_recall
0.2964376457893012 [0.284404,0.020408,0.2,0.241935,0.16129,0.870588]
unweighted_recall
0.2926716066716713 [0.192661,0.102041,0.093333,0.274194,0.274194,0.819608]
unweighted_recall
0.2995768244751103 [0.211009,0.061224,0.226667,0.229508,0.209677,0.859375]
unweighted_recall
0.32059530314978507 [0.440367,0.020833,0.2,0.196721,0.225806,0.839844]
unweighted_recall
0.30342001313669986 [0.266055,0.083333,0.175676,0.213115,0.269841,0.8125]
usercpu_time_millis
437.5
usercpu_time_millis
406.25
usercpu_time_millis
359.375
usercpu_time_millis
359.375
usercpu_time_millis
359.375
usercpu_time_millis
359.375
usercpu_time_millis
390.625
usercpu_time_millis
421.875
usercpu_time_millis
375
usercpu_time_millis
375
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
0
usercpu_time_millis_testing
0
usercpu_time_millis_testing
0
usercpu_time_millis_testing
0
usercpu_time_millis_testing
0
usercpu_time_millis_training
437.5
usercpu_time_millis_training
406.25
usercpu_time_millis_training
359.375
usercpu_time_millis_training
359.375
usercpu_time_millis_training
359.375
usercpu_time_millis_training
359.375
usercpu_time_millis_training
390.625
usercpu_time_millis_training
421.875
usercpu_time_millis_training
375
usercpu_time_millis_training
375
wall_clock_time_millis
426.14054679870605
wall_clock_time_millis
408.9550971984863
wall_clock_time_millis
354.5713424682617
wall_clock_time_millis
367.54679679870605
wall_clock_time_millis
364.4289970397949
wall_clock_time_millis
359.5871925354004
wall_clock_time_millis
401.8442630767822
wall_clock_time_millis
429.87966537475586
wall_clock_time_millis
375.69332122802734
wall_clock_time_millis
391.0212516784668
wall_clock_time_millis_testing
2.044200897216797
wall_clock_time_millis_testing
2.1734237670898438
wall_clock_time_millis_testing
2.1491050720214844
wall_clock_time_millis_testing
2.093076705932617
wall_clock_time_millis_testing
2.315521240234375
wall_clock_time_millis_testing
2.284526824951172
wall_clock_time_millis_testing
2.156972885131836
wall_clock_time_millis_testing
2.1774768829345703
wall_clock_time_millis_testing
2.012491226196289
wall_clock_time_millis_testing
2.1033287048339844
wall_clock_time_millis_training
424.09634590148926
wall_clock_time_millis_training
406.7816734313965
wall_clock_time_millis_training
352.42223739624023
wall_clock_time_millis_training
365.45372009277344
wall_clock_time_millis_training
362.11347579956055
wall_clock_time_millis_training
357.3026657104492
wall_clock_time_millis_training
399.6872901916504
wall_clock_time_millis_training
427.7021884918213
wall_clock_time_millis_training
373.68083000183105
wall_clock_time_millis_training
388.9179229736328
weighted_recall
0.46078431372549017 [0.211009,0.104167,0.121622,0.258065,0.349206,0.808594]
weighted_recall
0.4526143790849673 [0.293578,0.041667,0.12,0.225806,0.174603,0.819608]
weighted_recall
0.45098039215686275 [0.222222,0.122449,0.106667,0.258065,0.253968,0.807843]
weighted_recall
0.4493464052287582 [0.174312,0.163265,0.16,0.129032,0.16129,0.854902]
weighted_recall
0.4591503267973856 [0.321101,0.040816,0.213333,0.225806,0.403226,0.741176]
weighted_recall
0.4803921568627451 [0.284404,0.020408,0.2,0.241935,0.16129,0.870588]
weighted_recall
0.45098039215686275 [0.192661,0.102041,0.093333,0.274194,0.274194,0.819608]
weighted_recall
0.4738562091503268 [0.211009,0.061224,0.226667,0.229508,0.209677,0.859375]
weighted_recall
0.49918166939443537 [0.440367,0.020833,0.2,0.196721,0.225806,0.839844]
weighted_recall
0.46481178396072015 [0.266055,0.083333,0.175676,0.213115,0.269841,0.8125]