10560713
6691
Sergey Redyuk
14970
Supervised Classification
18968
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,svc=sklearn.svm.classes.SVC)(2)
8277063
Python_3.6.14. Sklearn_0.20.0. NumPy_1.19.5. SciPy_1.5.4.
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": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "nominal", "step_name": "nominal", "argument_1": []}}]
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
memory
null
18968
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": "svc", "step_name": "svc"}}]
18968
C
143.11841724167172
18969
cache_size
200
18969
class_weight
null
18969
coef0
0.22921525238301776
18969
decision_function_shape
"ovr"
18969
degree
2
18969
gamma
0.0070192306738709525
18969
kernel
"poly"
18969
max_iter
-1
18969
probability
false
18969
random_state
7774
18969
shrinking
false
18969
tol
1.1571247532842242e-05
18969
verbose
false
18969
openml-python
Sklearn_0.20.0.
1478
har
https://www.openml.org/data/download/1589271/php88ZB4Q
-1
22047524
description
https://api.openml.org/data/download/22047524/description.xml
-1
22047525
predictions
https://api.openml.org/data/download/22047525/predictions.arff
area_under_roc_curve
0.9938553708521116 [0.999883,0.999943,0.999289,0.982658,0.983643,1]
average_cost
0
f_measure
0.9899006485473122 [0.99942,0.999676,0.999288,0.9713,0.973498,1]
kappa
0.9878523872750974
kb_relative_information_score
0.9891223203090024
mean_absolute_error
0.00336602259119008
mean_prior_absolute_error
0.27709458719152297
weighted_recall
0.9899019322264297 [1,1,0.998578,0.9713,0.973242,1]
number_of_instances
10299 [1722,1544,1406,1777,1906,1944]
precision
0.9898996718822842 [0.99884,0.999353,1,0.9713,0.973753,1]
predictive_accuracy
0.9899019322264297
prior_entropy
2.575922879508845
relative_absolute_error
0.012147558078655444
root_mean_prior_squared_error
0.3722191487615371
root_mean_squared_error
0.05801743351088602
root_relative_squared_error
0.1558690188399066
total_cost
0
unweighted_recall
0.9905199768439342 [1,1,0.998578,0.9713,0.973242,1]
area_under_roc_curve
0.9964515939498734 [1,1,1,0.989812,0.990359,1]
area_under_roc_curve
0.9934941462371838 [0.999417,1,0.996429,0.980799,0.985953,1]
area_under_roc_curve
0.9911153452299015 [1,1,1,0.971198,0.97893,1]
area_under_roc_curve
0.995271629778672 [1,1,1,0.986417,0.987093,1]
area_under_roc_curve
0.9941139990628705 [1,0.999429,1,0.983021,0.984461,1]
area_under_roc_curve
0.9958752515090544 [1,1,1,0.991448,0.985652,1]
area_under_roc_curve
0.995271629778672 [1,1,1,0.986417,0.987093,1]
area_under_roc_curve
0.9905528688621943 [1,1,1,0.97495,0.972268,1]
area_under_roc_curve
0.9935032633892579 [1,1,1,0.982359,0.981313,1]
area_under_roc_curve
0.9929023448604655 [0.999417,1,0.996429,0.980117,0.983331,1]
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
0.9941747572815534 [1,1,1,0.983146,0.984293,1]
f_measure
0.9893179128541388 [0.997101,1,0.996416,0.971751,0.973958,1]
f_measure
0.9854317496909428 [1,1,1,0.957507,0.961039,1]
f_measure
0.9922330097087378 [1,1,1,0.977528,0.978947,1]
f_measure
0.9902813056039358 [1,0.996764,1,0.97191,0.976253,1]
f_measure
0.9932052392737646 [1,1,1,0.980501,0.981432,1]
f_measure
0.9922330097087378 [1,1,1,0.977528,0.978947,1]
f_measure
0.984468775298123 [1,1,1,0.955056,0.957895,1]
f_measure
0.9893214148176781 [1,1,1,0.969014,0.971129,1]
f_measure
0.9883366732142264 [0.997101,1,0.996416,0.968839,0.971279,1]
kappa
0.9929923233056276
kappa
0.9871517477251902
kappa
0.9824800334750429
kappa
0.9906574904477374
kappa
0.9883218630596718
kappa
0.9918253041417704
kappa
0.9906566429681033
kappa
0.981313328313936
kappa
0.987152709270233
kappa
0.9859691384678319
kb_relative_information_score
0.993738559768109
kb_relative_information_score
0.9883718959985324
kb_relative_information_score
0.9843017027330903
kb_relative_information_score
0.9916527932017111
kb_relative_information_score
0.9895653728861863
kb_relative_information_score
0.9927404529678726
kb_relative_information_score
0.9916517481954997
kb_relative_information_score
0.983332658201206
kb_relative_information_score
0.9885356154389495
kb_relative_information_score
0.9873295287532646
mean_absolute_error
0.0019417475728155337
mean_absolute_error
0.0035598705501618125
mean_absolute_error
0.004854368932038834
mean_absolute_error
0.0025889967637540453
mean_absolute_error
0.003236245954692557
mean_absolute_error
0.002265372168284789
mean_absolute_error
0.0025889967637540453
mean_absolute_error
0.00517799352750809
mean_absolute_error
0.0035598705501618125
mean_absolute_error
0.003887269193391642
mean_prior_absolute_error
0.27709199511972005
mean_prior_absolute_error
0.27709199511972005
mean_prior_absolute_error
0.27709199511972005
mean_prior_absolute_error
0.2771076974290587
mean_prior_absolute_error
0.27710210740693414
mean_prior_absolute_error
0.27710210740693414
mean_prior_absolute_error
0.27709513558158777
mean_prior_absolute_error
0.2770910843857784
mean_prior_absolute_error
0.2770910843857784
mean_prior_absolute_error
0.27708065643484137
number_of_instances
1030 [172,155,140,178,191,194]
number_of_instances
1030 [172,155,140,178,191,194]
number_of_instances
1030 [172,155,140,178,191,194]
number_of_instances
1030 [172,155,141,178,190,194]
number_of_instances
1030 [173,154,141,178,190,194]
number_of_instances
1030 [173,154,141,178,190,194]
number_of_instances
1030 [172,154,141,178,190,195]
number_of_instances
1030 [172,154,141,177,191,195]
number_of_instances
1030 [172,154,141,177,191,195]
number_of_instances
1029 [172,154,140,177,191,195]
precision
0.9941747572815534 [1,1,1,0.983146,0.984293,1]
precision
0.9893422349195818 [0.99422,1,1,0.977273,0.968912,1]
precision
0.9854721535095872 [1,1,1,0.965714,0.953608,1]
precision
0.9922330097087378 [1,1,1,0.977528,0.978947,1]
precision
0.990276978244407 [1,0.993548,1,0.97191,0.978836,1]
precision
0.9932531916181354 [1,1,1,0.972376,0.989305,1]
precision
0.9922330097087378 [1,1,1,0.977528,0.978947,1]
precision
0.9844917326069358 [1,1,1,0.949721,0.962963,1]
precision
0.9893275651220338 [1,1,1,0.966292,0.973684,1]
precision
0.9883465707054536 [0.99422,1,1,0.971591,0.96875,1]
predictive_accuracy
0.9941747572815534
predictive_accuracy
0.9893203883495145
predictive_accuracy
0.9854368932038835
predictive_accuracy
0.9922330097087378
predictive_accuracy
0.9902912621359223
predictive_accuracy
0.9932038834951455
predictive_accuracy
0.9922330097087378
predictive_accuracy
0.9844660194174757
predictive_accuracy
0.9893203883495145
predictive_accuracy
0.9883381924198251
prior_entropy
2.5758425283766972
prior_entropy
2.5758425283766972
prior_entropy
2.5758425283766972
prior_entropy
2.57626843373114
prior_entropy
2.5761156998831467
prior_entropy
2.5761156998831467
prior_entropy
2.575945945073779
prior_entropy
2.575847838744184
prior_entropy
2.575847838744184
prior_entropy
2.5755594010061413
relative_absolute_error
0.007007591727709725
relative_absolute_error
0.012847251500801167
relative_absolute_error
0.01751897931927431
relative_absolute_error
0.00934292618997653
relative_absolute_error
0.011678893332774321
relative_absolute_error
0.008175225332942022
relative_absolute_error
0.009343349742751951
relative_absolute_error
0.01868697269342329
relative_absolute_error
0.012847293726728517
relative_absolute_error
0.014029377739350696
root_mean_prior_squared_error
0.37221566682901186
root_mean_prior_squared_error
0.37221566682901186
root_mean_prior_squared_error
0.37221566682901186
root_mean_prior_squared_error
0.3722367592572026
root_mean_prior_squared_error
0.3722292504897755
root_mean_prior_squared_error
0.3722292504897755
root_mean_prior_squared_error
0.3722198854102689
root_mean_prior_squared_error
0.37221444343150406
root_mean_prior_squared_error
0.37221444343150406
root_mean_prior_squared_error
0.3722004351798735
root_mean_squared_error
0.04406526492392317
root_mean_squared_error
0.05966465075873496
root_mean_squared_error
0.06967330142916175
root_mean_squared_error
0.050882185131478436
root_mean_squared_error
0.05688801239885743
root_mean_squared_error
0.04759592596309887
root_mean_squared_error
0.050882185131478436
root_mean_squared_error
0.07195827629611544
root_mean_squared_error
0.05966465075873496
root_mean_squared_error
0.062347968638854966
root_relative_squared_error
0.11838637878766622
root_relative_squared_error
0.16029591464279677
root_relative_squared_error
0.1871853004542343
root_relative_squared_error
0.1366930693062493
root_relative_squared_error
0.1528305804124871
root_relative_squared_error
0.1278672374631296
root_relative_squared_error
0.13669926601421356
root_relative_squared_error
0.19332478243649187
root_relative_squared_error
0.16029644150473335
root_relative_squared_error
0.16751181015874964
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
0.9945732101888347 [1,1,1,0.983146,0.984293,1]
unweighted_recall
0.9897011448852734 [1,1,0.992857,0.966292,0.979058,1]
unweighted_recall
0.9863374316136243 [1,1,1,0.949438,0.968586,1]
unweighted_recall
0.9927459097181156 [1,1,1,0.977528,0.978947,1]
unweighted_recall
0.9909323871476444 [1,1,1,0.97191,0.973684,1]
unweighted_recall
0.9937413759116893 [1,1,1,0.988764,0.973684,1]
unweighted_recall
0.9927459097181156 [1,1,1,0.977528,0.978947,1]
unweighted_recall
0.9855552597588271 [1,1,1,0.960452,0.95288,1]
unweighted_recall
0.9900562999773223 [1,1,1,0.971751,0.968586,1]
unweighted_recall
0.9887968045501988 [1,1,0.992857,0.966102,0.973822,1]
usercpu_time_millis
6437.5
usercpu_time_millis
6375
usercpu_time_millis
5468.75
usercpu_time_millis
6015.625
usercpu_time_millis
6203.125
usercpu_time_millis
7015.625
usercpu_time_millis
5562.5
usercpu_time_millis
5328.125
usercpu_time_millis
5656.25
usercpu_time_millis
6250
usercpu_time_millis_testing
843.75
usercpu_time_millis_testing
781.25
usercpu_time_millis_testing
609.375
usercpu_time_millis_testing
781.25
usercpu_time_millis_testing
718.75
usercpu_time_millis_testing
906.25
usercpu_time_millis_testing
593.75
usercpu_time_millis_testing
640.625
usercpu_time_millis_testing
671.875
usercpu_time_millis_testing
734.375
usercpu_time_millis_training
5593.75
usercpu_time_millis_training
5593.75
usercpu_time_millis_training
4859.375
usercpu_time_millis_training
5234.375
usercpu_time_millis_training
5484.375
usercpu_time_millis_training
6109.375
usercpu_time_millis_training
4968.75
usercpu_time_millis_training
4687.5
usercpu_time_millis_training
4984.375
usercpu_time_millis_training
5515.625
wall_clock_time_millis
6581.904888153076
wall_clock_time_millis
6396.24285697937
wall_clock_time_millis
5496.058464050293
wall_clock_time_millis
6026.663303375244
wall_clock_time_millis
6295.251369476318
wall_clock_time_millis
7180.100202560425
wall_clock_time_millis
5568.552732467651
wall_clock_time_millis
5317.663192749023
wall_clock_time_millis
5678.145170211792
wall_clock_time_millis
6280.928134918213
wall_clock_time_millis_testing
879.8716068267822
wall_clock_time_millis_testing
788.4914875030518
wall_clock_time_millis_testing
607.414722442627
wall_clock_time_millis_testing
792.0751571655273
wall_clock_time_millis_testing
716.4614200592041
wall_clock_time_millis_testing
1013.031005859375
wall_clock_time_millis_testing
608.0517768859863
wall_clock_time_millis_testing
640.0790214538574
wall_clock_time_millis_testing
671.4239120483398
wall_clock_time_millis_testing
734.6484661102295
wall_clock_time_millis_training
5702.033281326294
wall_clock_time_millis_training
5607.751369476318
wall_clock_time_millis_training
4888.643741607666
wall_clock_time_millis_training
5234.588146209717
wall_clock_time_millis_training
5578.789949417114
wall_clock_time_millis_training
6167.06919670105
wall_clock_time_millis_training
4960.500955581665
wall_clock_time_millis_training
4677.584171295166
wall_clock_time_millis_training
5006.721258163452
wall_clock_time_millis_training
5546.279668807983
weighted_recall
0.9941747572815534 [1,1,1,0.983146,0.984293,1]
weighted_recall
0.9893203883495145 [1,1,0.992857,0.966292,0.979058,1]
weighted_recall
0.9854368932038835 [1,1,1,0.949438,0.968586,1]
weighted_recall
0.9922330097087378 [1,1,1,0.977528,0.978947,1]
weighted_recall
0.9902912621359223 [1,1,1,0.97191,0.973684,1]
weighted_recall
0.9932038834951457 [1,1,1,0.988764,0.973684,1]
weighted_recall
0.9922330097087378 [1,1,1,0.977528,0.978947,1]
weighted_recall
0.9844660194174757 [1,1,1,0.960452,0.95288,1]
weighted_recall
0.9893203883495145 [1,1,1,0.971751,0.968586,1]
weighted_recall
0.9883381924198251 [1,1,0.992857,0.966102,0.973822,1]