10437824
11497
Fares Gaaloul
35
Supervised Classification
predictive_accuracy
17593
sklearn.pipeline.Pipeline(Imputer=sklearn.impute.SimpleImputer,fs=sklearn.feature_selection.univariate_selection.SelectPercentile,rf=sklearn.ensemble.forest.RandomForestClassifier)(2)
8260898
copy
true
17467
fill_value
null
17467
missing_values
NaN
17467
strategy
"constant"
17467
verbose
0
17467
bootstrap
true
17478
class_weight
null
17478
criterion
"gini"
17478
max_depth
null
17478
max_features
"auto"
17478
max_leaf_nodes
null
17478
min_impurity_decrease
0.0
17478
min_impurity_split
null
17478
min_samples_leaf
1
17478
min_samples_split
2
17478
min_weight_fraction_leaf
0.0
17478
n_estimators
100
17478
n_jobs
null
17478
oob_score
false
17478
random_state
31461
17478
verbose
0
17478
warm_start
false
17478
memory
null
17593
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "Imputer", "step_name": "Imputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "fs", "step_name": "fs"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "rf", "step_name": "rf"}}]
17593
percentile
80
17594
score_func
{"oml-python:serialized_object": "function", "value": "sklearn.feature_selection.univariate_selection.f_classif"}
17594
openml-python
Sklearn_0.20.3.
35
dermatology
https://www.openml.org/data/download/35/dataset_35_dermatology.arff
-1
21800001
description
https://api.openml.org/data/download/21800001/description.xml
-1
21800002
predictions
https://api.openml.org/data/download/21800002/predictions.arff
area_under_roc_curve
0.9991492710116312 [1,0.99699,1,0.997393,1,1]
average_cost
0
f_measure
0.9753004004657782 [0.99115,0.934426,1,0.927835,1,0.974359]
kappa
0.9691708704970657
kb_relative_information_score
0.9355860032823
mean_absolute_error
0.02822404371584699
mean_prior_absolute_error
0.2664473039935758
weighted_recall
0.9754098360655737 [1,0.934426,1,0.918367,1,0.95]
number_of_instances
366 [112,61,72,49,52,20]
precision
0.9753349391237657 [0.982456,0.934426,1,0.9375,1,1]
predictive_accuracy
0.9754098360655737
prior_entropy
2.432654569700141
relative_absolute_error
0.10592730079388414
root_mean_prior_squared_error
0.3648729603686826
root_mean_squared_error
0.0893117786572504
root_relative_squared_error
0.2447749994052892
total_cost
0
unweighted_recall
0.967132262741162 [1,0.934426,1,0.918367,1,0.95]
area_under_roc_curve
1 [1,1,1,1,1,1]
area_under_roc_curve
0.9973844812554491 [1,0.983871,1,1,1,1]
area_under_roc_curve
1 [1,1,1,1,1,1]
area_under_roc_curve
0.9982835658238884 [1,0.994624,1,0.99375,1,1]
area_under_roc_curve
1 [1,1,1,1,1,1]
area_under_roc_curve
1 [1,1,1,1,1,1]
area_under_roc_curve
1 [1,1,1,1,1,1]
area_under_roc_curve
1 [1,1,1,1,1,1]
area_under_roc_curve
0.9954301075268818 [1,0.983333,1,0.987097,1,1]
area_under_roc_curve
1 [1,1,1,1,1,1]
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
0.9725109725109725 [1,0.923077,1,0.888889,1,1]
f_measure
0.9725109725109725 [1,0.923077,1,0.888889,1,1]
f_measure
0.9690560125342734 [0.956522,1,1,1,1,0.666667]
f_measure
0.9725109725109725 [1,0.923077,1,0.888889,1,1]
f_measure
0.972972972972973 [1,0.909091,1,0.909091,1,1]
f_measure
0.9731619731619732 [1,0.923077,1,0.909091,1,1]
f_measure
0.9715634606938954 [0.956522,0.909091,1,1,1,1]
f_measure
1 [1,1,1,1,1,1]
f_measure
0.9444444444444444 [1,0.833333,1,0.8,1,1]
f_measure
1 [1,1,1,1,1,1]
kappa
0.9662716499544212
kappa
0.9661482159194877
kappa
0.9658986175115208
kappa
0.9658986175115208
kappa
0.9659613615455382
kappa
0.9663023679417123
kappa
0.965082444228904
kappa
1
kappa
0.9305019305019304
kappa
1
kb_relative_information_score
0.9358356478023357
kb_relative_information_score
0.9335759217774374
kb_relative_information_score
0.9181815076630646
kb_relative_information_score
0.9365674005328526
kb_relative_information_score
0.9380759707333162
kb_relative_information_score
0.9515931792975197
kb_relative_information_score
0.9430012127805351
kb_relative_information_score
0.9404229983937604
kb_relative_information_score
0.8910146156982663
kb_relative_information_score
0.9675944876427722
mean_absolute_error
0.029549549549549546
mean_absolute_error
0.026306306306306315
mean_absolute_error
0.03468468468468469
mean_absolute_error
0.02783783783783783
mean_absolute_error
0.027387387387387385
mean_absolute_error
0.02288288288288288
mean_absolute_error
0.02546296296296297
mean_absolute_error
0.028888888888888895
mean_absolute_error
0.04314814814814816
mean_absolute_error
0.01611111111111111
mean_prior_absolute_error
0.26707352513804133
mean_prior_absolute_error
0.2665891698149763
mean_prior_absolute_error
0.2665891698149763
mean_prior_absolute_error
0.2656204591688463
mean_prior_absolute_error
0.2656204591688463
mean_prior_absolute_error
0.2668555652426621
mean_prior_absolute_error
0.26655217045002
mean_prior_absolute_error
0.26655217045002
mean_prior_absolute_error
0.26655217045002
mean_prior_absolute_error
0.2664774990043808
number_of_instances
37 [11,6,7,5,6,2]
number_of_instances
37 [11,6,8,5,5,2]
number_of_instances
37 [11,6,8,5,5,2]
number_of_instances
37 [12,6,7,5,5,2]
number_of_instances
37 [12,6,7,5,5,2]
number_of_instances
37 [11,7,7,5,5,2]
number_of_instances
36 [11,6,7,5,5,2]
number_of_instances
36 [11,6,7,5,5,2]
number_of_instances
36 [11,6,7,5,5,2]
number_of_instances
36 [11,6,7,4,6,2]
precision
0.9768339768339768 [1,0.857143,1,1,1,1]
precision
0.9768339768339768 [1,0.857143,1,1,1,1]
precision
0.9752252252252251 [0.916667,1,1,1,1,1]
precision
0.9768339768339768 [1,0.857143,1,1,1,1]
precision
0.9774774774774776 [1,1,1,0.833333,1,1]
precision
0.9774774774774776 [1,1,1,0.833333,1,1]
precision
0.9745370370370369 [0.916667,1,1,1,1,1]
precision
1 [1,1,1,1,1,1]
precision
0.9444444444444444 [1,0.833333,1,0.8,1,1]
precision
1 [1,1,1,1,1,1]
predictive_accuracy
0.9729729729729729
predictive_accuracy
0.9729729729729729
predictive_accuracy
0.9729729729729729
predictive_accuracy
0.9729729729729729
predictive_accuracy
0.9729729729729729
predictive_accuracy
0.9729729729729729
predictive_accuracy
0.9722222222222223
predictive_accuracy
1
predictive_accuracy
0.9444444444444444
predictive_accuracy
1
prior_entropy
2.4459870034632
prior_entropy
2.4335031087519345
prior_entropy
2.4335031087519345
prior_entropy
2.416466503250984
prior_entropy
2.416466503250984
prior_entropy
2.4398714397922903
prior_entropy
2.435841132544266
prior_entropy
2.435841132544266
prior_entropy
2.435841132544266
prior_entropy
2.4335060140779197
relative_absolute_error
0.11064200217627851
relative_absolute_error
0.09867732558139534
relative_absolute_error
0.13010537790697674
relative_absolute_error
0.1048030634573304
relative_absolute_error
0.10310722100656453
relative_absolute_error
0.08575006806425263
relative_absolute_error
0.09552712671584647
relative_absolute_error
0.10837986740125126
relative_absolute_error
0.1618750583621253
relative_absolute_error
0.0604595553895012
root_mean_prior_squared_error
0.36573008948221786
root_mean_prior_squared_error
0.3650673130117323
root_mean_prior_squared_error
0.3650673130117323
root_mean_prior_squared_error
0.36373813710343333
root_mean_prior_squared_error
0.36373813710343333
root_mean_prior_squared_error
0.3654319888259535
root_mean_prior_squared_error
0.3650166347779916
root_mean_prior_squared_error
0.3650166347779916
root_mean_prior_squared_error
0.3650166347779916
root_mean_prior_squared_error
0.3649143354528711
root_mean_squared_error
0.09071785783256639
root_mean_squared_error
0.0956344391207788
root_mean_squared_error
0.09835585327713788
root_mean_squared_error
0.08963891529428017
root_mean_squared_error
0.08334234185542153
root_mean_squared_error
0.07495944849662996
root_mean_squared_error
0.08129165598838133
root_mean_squared_error
0.07409328454600198
root_mean_squared_error
0.1308129849710534
root_mean_squared_error
0.05396329342281694
root_relative_squared_error
0.24804592359627872
root_relative_squared_error
0.2619638508082628
root_relative_squared_error
0.269418405240726
root_relative_squared_error
0.24643804471014338
root_relative_squared_error
0.22912731262964084
root_relative_squared_error
0.20512557955710697
root_relative_squared_error
0.22270671592220473
root_relative_squared_error
0.2029860490907944
root_relative_squared_error
0.3583754067828053
root_relative_squared_error
0.14787934641111497
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
0.9666666666666667 [1,1,1,0.8,1,1]
unweighted_recall
0.9666666666666667 [1,1,1,0.8,1,1]
unweighted_recall
0.9166666666666666 [1,1,1,1,1,0.5]
unweighted_recall
0.9666666666666667 [1,1,1,0.8,1,1]
unweighted_recall
0.9722222222222223 [1,0.833333,1,1,1,1]
unweighted_recall
0.9761904761904763 [1,0.857143,1,1,1,1]
unweighted_recall
0.9722222222222223 [1,0.833333,1,1,1,1]
unweighted_recall
1 [1,1,1,1,1,1]
unweighted_recall
0.938888888888889 [1,0.833333,1,0.8,1,1]
unweighted_recall
1 [1,1,1,1,1,1]
usercpu_time_millis
112.24447699999995
usercpu_time_millis
109.20125000000081
usercpu_time_millis
108.32854900000032
usercpu_time_millis
110.26640600000005
usercpu_time_millis
111.8374830000004
usercpu_time_millis
108.51104199999995
usercpu_time_millis
112.17435799999987
usercpu_time_millis
119.8005550000003
usercpu_time_millis
113.36998100000083
usercpu_time_millis
108.5822900000002
usercpu_time_millis_testing
5.559814999999801
usercpu_time_millis_testing
5.265407000000444
usercpu_time_millis_testing
5.112720000000515
usercpu_time_millis_testing
5.0301070000005055
usercpu_time_millis_testing
5.158050000000358
usercpu_time_millis_testing
5.430389999999896
usercpu_time_millis_testing
5.04270600000023
usercpu_time_millis_testing
5.086979999999741
usercpu_time_millis_testing
5.128936000000195
usercpu_time_millis_testing
4.988379999999459
usercpu_time_millis_training
106.68466200000015
usercpu_time_millis_training
103.93584300000036
usercpu_time_millis_training
103.21582899999981
usercpu_time_millis_training
105.23629899999953
usercpu_time_millis_training
106.67943300000005
usercpu_time_millis_training
103.08065200000004
usercpu_time_millis_training
107.13165199999963
usercpu_time_millis_training
114.71357500000056
usercpu_time_millis_training
108.24104500000064
usercpu_time_millis_training
103.59391000000073
wall_clock_time_millis
112.55288124084473
wall_clock_time_millis
110.0614070892334
wall_clock_time_millis
108.56342315673828
wall_clock_time_millis
110.9015941619873
wall_clock_time_millis
111.95778846740723
wall_clock_time_millis
108.59274864196777
wall_clock_time_millis
112.28132247924805
wall_clock_time_millis
119.81391906738281
wall_clock_time_millis
113.53421211242676
wall_clock_time_millis
108.7028980255127
wall_clock_time_millis_testing
5.562543869018555
wall_clock_time_millis_testing
5.269050598144531
wall_clock_time_millis_testing
5.115985870361328
wall_clock_time_millis_testing
5.0334930419921875
wall_clock_time_millis_testing
5.161523818969727
wall_clock_time_millis_testing
5.433797836303711
wall_clock_time_millis_testing
5.045175552368164
wall_clock_time_millis_testing
5.0907135009765625
wall_clock_time_millis_testing
5.13148307800293
wall_clock_time_millis_testing
4.990816116333008
wall_clock_time_millis_training
106.99033737182617
wall_clock_time_millis_training
104.79235649108887
wall_clock_time_millis_training
103.44743728637695
wall_clock_time_millis_training
105.86810111999512
wall_clock_time_millis_training
106.7962646484375
wall_clock_time_millis_training
103.15895080566406
wall_clock_time_millis_training
107.23614692687988
wall_clock_time_millis_training
114.72320556640625
wall_clock_time_millis_training
108.40272903442383
wall_clock_time_millis_training
103.71208190917969
weighted_recall
0.972972972972973 [1,1,1,0.8,1,1]
weighted_recall
0.972972972972973 [1,1,1,0.8,1,1]
weighted_recall
0.972972972972973 [1,1,1,1,1,0.5]
weighted_recall
0.972972972972973 [1,1,1,0.8,1,1]
weighted_recall
0.972972972972973 [1,0.833333,1,1,1,1]
weighted_recall
0.972972972972973 [1,0.857143,1,1,1,1]
weighted_recall
0.9722222222222222 [1,0.833333,1,1,1,1]
weighted_recall
1 [1,1,1,1,1,1]
weighted_recall
0.9444444444444444 [1,0.833333,1,0.8,1,1]
weighted_recall
1 [1,1,1,1,1,1]