10590770
32117
VAIBHAV JAISWAL
37
Supervised Classification
19161
sklearn.pipeline.Pipeline(numerical=sklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,scaler=sklearn.preprocessing._data.StandardScaler),model=sklearn.neighbors._classification.KNeighborsClassifier)(1)
8304079
Python_3.7.7. Sklearn_1.0.2. NumPy_1.21.6. SciPy_1.7.3.
copy
true
19075
with_mean
true
19075
with_std
true
19075
add_indicator
false
19084
copy
true
19084
fill_value
null
19084
missing_values
NaN
19084
strategy
"mean"
19084
verbose
0
19084
algorithm
"auto"
19154
leaf_size
30
19154
metric
"minkowski"
19154
metric_params
null
19154
n_jobs
null
19154
n_neighbors
5
19154
p
2
19154
weights
"uniform"
19154
memory
null
19156
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "Imputer", "step_name": "Imputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "scaler", "step_name": "scaler"}}]
19156
verbose
false
19156
memory
null
19161
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "numerical", "step_name": "numerical"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "model", "step_name": "model"}}]
19161
verbose
false
19161
openml-python
Sklearn_1.0.2.
37
diabetes
https://www.openml.org/data/download/37/dataset_37_diabetes.arff
-1
22109136
description
https://api.openml.org/data/download/22109136/description.xml
-1
22109137
predictions
https://api.openml.org/data/download/22109137/predictions.arff
area_under_roc_curve
0.7767761194029851 [0.776776,0.776776]
average_cost
0
f_measure
0.7370703913921582 [0.809249,0.60241]
kappa
0.41329711710599415
kb_relative_information_score
0.29979491757787846
mean_absolute_error
0.31614583333333285
mean_prior_absolute_error
0.4544913419913401
weighted_recall
0.7421875 [0.84,0.559701]
number_of_instances
768 [500,268]
precision
0.735829663003071 [0.780669,0.652174]
predictive_accuracy
0.7421875
prior_entropy
0.9331348051619819
relative_absolute_error
0.6956036432908698
root_mean_prior_squared_error
0.4766409223329586
root_mean_squared_error
0.4289036410819257
root_relative_squared_error
0.8998464483129589
total_cost
0
unweighted_recall
0.6998507462686567 [0.84,0.559701]
area_under_roc_curve
0.8818518518518519 [0.881852,0.881852]
area_under_roc_curve
0.6688888888888889 [0.668889,0.668889]
area_under_roc_curve
0.8288888888888888 [0.828889,0.828889]
area_under_roc_curve
0.762962962962963 [0.762963,0.762963]
area_under_roc_curve
0.7359259259259259 [0.735926,0.735926]
area_under_roc_curve
0.7377777777777778 [0.737778,0.737778]
area_under_roc_curve
0.8185185185185185 [0.818519,0.818519]
area_under_roc_curve
0.7755555555555557 [0.775556,0.775556]
area_under_roc_curve
0.7530769230769231 [0.753077,0.753077]
area_under_roc_curve
0.7826923076923077 [0.782692,0.782692]
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
0.8043214024906533 [0.851485,0.716981]
f_measure
0.6670602125147579 [0.781818,0.454545]
f_measure
0.7640300875594993 [0.823529,0.653846]
f_measure
0.7045148247978437 [0.792453,0.541667]
f_measure
0.7198515769944341 [0.8,0.571429]
f_measure
0.6531558512025142 [0.721649,0.526316]
f_measure
0.7582394021073267 [0.830189,0.625]
f_measure
0.7387584892172047 [0.825688,0.577778]
f_measure
0.7697435077054338 [0.838095,0.638298]
f_measure
0.7789572337591871 [0.824742,0.690909]
kappa
0.5685468808367576
kappa
0.25182186234817816
kappa
0.4777694046721929
kappa
0.33879781420765026
kappa
0.3744680851063831
kappa
0.24918743228602383
kappa
0.459016393442623
kappa
0.4131568391496189
kappa
0.47903225806451605
kappa
0.5164670658682634
kb_relative_information_score
0.44238823847581804
kb_relative_information_score
0.19014070273683867
kb_relative_information_score
0.3665309887126845
kb_relative_information_score
0.2689008067407496
kb_relative_information_score
0.23997595158358428
kb_relative_information_score
0.20998549646934378
kb_relative_information_score
0.35479277745255267
kb_relative_information_score
0.31237717265319076
kb_relative_information_score
0.27296346790669895
kb_relative_information_score
0.3401792994684248
mean_absolute_error
0.25454545454545446
mean_absolute_error
0.3610389610389608
mean_absolute_error
0.2883116883116882
mean_absolute_error
0.3298701298701297
mean_absolute_error
0.34285714285714264
mean_absolute_error
0.3480519480519481
mean_absolute_error
0.2935064935064934
mean_absolute_error
0.31688311688311666
mean_absolute_error
0.3289473684210524
mean_absolute_error
0.29736842105263156
mean_prior_absolute_error
0.4550008433125322
mean_prior_absolute_error
0.4550008433125322
mean_prior_absolute_error
0.4550008433125322
mean_prior_absolute_error
0.4550008433125322
mean_prior_absolute_error
0.4550008433125322
mean_prior_absolute_error
0.4550008433125322
mean_prior_absolute_error
0.4550008433125322
mean_prior_absolute_error
0.4550008433125322
mean_prior_absolute_error
0.45242652084757423
mean_prior_absolute_error
0.45242652084757423
number_of_instances
77 [50,27]
number_of_instances
77 [50,27]
number_of_instances
77 [50,27]
number_of_instances
77 [50,27]
number_of_instances
77 [50,27]
number_of_instances
77 [50,27]
number_of_instances
77 [50,27]
number_of_instances
77 [50,27]
number_of_instances
76 [50,26]
number_of_instances
76 [50,26]
precision
0.8037354802060683 [0.843137,0.730769]
precision
0.6716322892793481 [0.716667,0.588235]
precision
0.7629170829170829 [0.807692,0.68]
precision
0.7040816326530612 [0.75,0.619048]
precision
0.71900826446281 [0.763636,0.636364]
precision
0.6588836695219673 [0.744681,0.5]
precision
0.7606679035250463 [0.785714,0.714286]
precision
0.74851419766674 [0.762712,0.722222]
precision
0.7706766917293233 [0.8,0.714286]
precision
0.7840483453681893 [0.851064,0.655172]
predictive_accuracy
0.8051948051948052
predictive_accuracy
0.6883116883116882
predictive_accuracy
0.7662337662337663
predictive_accuracy
0.7142857142857143
predictive_accuracy
0.7272727272727273
predictive_accuracy
0.6493506493506493
predictive_accuracy
0.7662337662337663
predictive_accuracy
0.7532467532467533
predictive_accuracy
0.7763157894736843
predictive_accuracy
0.7763157894736843
prior_entropy
0.9346519933901933
prior_entropy
0.9346519933901933
prior_entropy
0.9346519933901933
prior_entropy
0.9346519933901933
prior_entropy
0.9346519933901933
prior_entropy
0.9346519933901933
prior_entropy
0.9346519933901933
prior_entropy
0.9346519933901933
prior_entropy
0.9269862002370954
prior_entropy
0.9269862002370954
relative_absolute_error
0.5594395225562507
relative_absolute_error
0.7934907513808044
relative_absolute_error
0.6336508877933043
relative_absolute_error
0.7249879527004471
relative_absolute_error
0.7535307854839293
relative_absolute_error
0.7649479185973227
relative_absolute_error
0.6450680209066972
relative_absolute_error
0.6964451199169649
relative_absolute_error
0.7270735760688909
relative_absolute_error
0.6572745127662778
root_mean_prior_squared_error
0.4771750938215478
root_mean_prior_squared_error
0.4771750938215478
root_mean_prior_squared_error
0.4771750938215478
root_mean_prior_squared_error
0.4771750938215478
root_mean_prior_squared_error
0.4771750938215478
root_mean_prior_squared_error
0.4771750938215478
root_mean_prior_squared_error
0.4771750938215478
root_mean_prior_squared_error
0.4771750938215478
root_mean_prior_squared_error
0.4744699650121647
root_mean_prior_squared_error
0.4744699650121647
root_mean_squared_error
0.3632465443029734
root_mean_squared_error
0.4775478489658894
root_mean_squared_error
0.3980471811752451
root_mean_squared_error
0.444884342185784
root_mean_squared_error
0.4454677973114985
root_mean_squared_error
0.44779401572540073
root_mean_squared_error
0.41840761831608053
root_mean_squared_error
0.4239578513723499
root_mean_squared_error
0.4358898943540672
root_mean_squared_error
0.4236433455284365
root_relative_squared_error
0.7612437216574822
root_relative_squared_error
1.000781170579035
root_relative_squared_error
0.8341742608303554
root_relative_squared_error
0.9323293439790471
root_relative_squared_error
0.9335520715129632
root_relative_squared_error
0.9384270502032218
root_relative_squared_error
0.8768429528984493
root_relative_squared_error
0.8884743920245346
root_relative_squared_error
0.9186880656247476
root_relative_squared_error
0.8928770560167595
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
0.7818518518518518 [0.86,0.703704]
unweighted_recall
0.6151851851851852 [0.86,0.37037]
unweighted_recall
0.7348148148148148 [0.84,0.62963]
unweighted_recall
0.6607407407407407 [0.84,0.481481]
unweighted_recall
0.6792592592592592 [0.84,0.518519]
unweighted_recall
0.6277777777777778 [0.7,0.555556]
unweighted_recall
0.7177777777777778 [0.88,0.555556]
unweighted_recall
0.6907407407407408 [0.9,0.481481]
unweighted_recall
0.7284615384615385 [0.88,0.576923]
unweighted_recall
0.7653846153846153 [0.8,0.730769]
usercpu_time_millis
15.625
usercpu_time_millis
15.625
usercpu_time_millis
15.625
usercpu_time_millis
15.625
usercpu_time_millis
15.625
usercpu_time_millis
15.625
usercpu_time_millis
15.625
usercpu_time_millis
15.625
usercpu_time_millis
15.625
usercpu_time_millis
15.625
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_testing
15.625
usercpu_time_millis_testing
15.625
usercpu_time_millis_testing
0
usercpu_time_millis_testing
15.625
usercpu_time_millis_testing
15.625
usercpu_time_millis_testing
15.625
usercpu_time_millis_training
15.625
usercpu_time_millis_training
15.625
usercpu_time_millis_training
0
usercpu_time_millis_training
0
usercpu_time_millis_training
0
usercpu_time_millis_training
0
usercpu_time_millis_training
15.625
usercpu_time_millis_training
0
usercpu_time_millis_training
0
usercpu_time_millis_training
0
wall_clock_time_millis
13.010263442993164
wall_clock_time_millis
12.970447540283203
wall_clock_time_millis
16.008615493774414
wall_clock_time_millis
15.990495681762695
wall_clock_time_millis
13.972282409667969
wall_clock_time_millis
13.988733291625977
wall_clock_time_millis
14.989137649536133
wall_clock_time_millis
14.98723030090332
wall_clock_time_millis
12.99595832824707
wall_clock_time_millis
13.01264762878418
wall_clock_time_millis_testing
6.014823913574219
wall_clock_time_millis_testing
6.996393203735352
wall_clock_time_millis_testing
6.994724273681641
wall_clock_time_millis_testing
6.973505020141602
wall_clock_time_millis_testing
6.977558135986328
wall_clock_time_millis_testing
6.974935531616211
wall_clock_time_millis_testing
7.017612457275391
wall_clock_time_millis_testing
5.9967041015625
wall_clock_time_millis_testing
6.976604461669922
wall_clock_time_millis_testing
5.995988845825195
wall_clock_time_millis_training
6.995439529418945
wall_clock_time_millis_training
5.974054336547852
wall_clock_time_millis_training
9.013891220092773
wall_clock_time_millis_training
9.016990661621094
wall_clock_time_millis_training
6.994724273681641
wall_clock_time_millis_training
7.013797760009766
wall_clock_time_millis_training
7.971525192260742
wall_clock_time_millis_training
8.99052619934082
wall_clock_time_millis_training
6.019353866577148
wall_clock_time_millis_training
7.016658782958984
weighted_recall
0.8051948051948052 [0.86,0.703704]
weighted_recall
0.6883116883116883 [0.86,0.37037]
weighted_recall
0.7662337662337663 [0.84,0.62963]
weighted_recall
0.7142857142857143 [0.84,0.481481]
weighted_recall
0.7272727272727273 [0.84,0.518519]
weighted_recall
0.6493506493506493 [0.7,0.555556]
weighted_recall
0.7662337662337663 [0.88,0.555556]
weighted_recall
0.7532467532467533 [0.9,0.481481]
weighted_recall
0.7763157894736842 [0.88,0.576923]
weighted_recall
0.7763157894736842 [0.8,0.730769]