10317725
8323
Heinrich Peters
3481
Supervised Classification
12736
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,histgradientboostingclassifier=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(1)
8155383
l2_regularization
1e-09
12677
learning_rate
0.1
12677
loss
"auto"
12677
max_bins
32
12677
max_depth
11
12677
max_iter
50
12677
max_leaf_nodes
16
12677
min_samples_leaf
8
12677
n_iter_no_change
null
12677
random_state
4137
12677
scoring
null
12677
tol
1e-07
12677
validation_fraction
0.1
12677
verbose
0
12677
memory
null
12736
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "histgradientboostingclassifier", "step_name": "histgradientboostingclassifier"}}]
12736
verbose
false
12736
add_indicator
false
12737
copy
true
12737
fill_value
null
12737
missing_values
NaN
12737
strategy
"most_frequent"
12737
verbose
0
12737
openml-python
Sklearn_0.21.2.
300
isolet
https://www.openml.org/data/download/52405/phpB0xrNj
-1
21557133
description
https://api.openml.org/data/download/21557133/description.xml
-1
21557134
predictions
https://api.openml.org/data/download/21557134/predictions.arff
area_under_roc_curve
0.9987319307814518 [0.999501,0.998274,0.999194,0.997623,0.998717,0.99884,0.998133,0.998405,0.998256,0.999277,0.999655,0.999918,0.998488,0.998555,0.999212,0.996546,0.99953,0.999859,0.99796,0.99615,0.999311,0.998279,0.999336,0.999765,0.99995,0.998296]
average_cost
0
f_measure
0.9526371795718499 [0.952998,0.894309,0.986755,0.917763,0.907563,0.946844,0.954469,0.979661,0.976589,0.9699,0.958124,0.978512,0.919463,0.92257,0.972881,0.903974,0.98,0.983444,0.964587,0.928814,0.963211,0.906667,0.975124,0.983333,0.989933,0.950931]
kappa
0.950647689520697
kb_relative_information_score
0.9577762276215133
mean_absolute_error
0.00476923134319116
mean_prior_absolute_error
0.07396449117237175
number_of_instances
7797 [300,300,300,300,300,298,300,300,300,300,300,300,299,300,300,300,300,300,300,300,300,300,300,300,300,300]
precision
0.9529855448633676 [0.927445,0.873016,0.980263,0.905844,0.915254,0.9375,0.96587,0.996552,0.979866,0.973154,0.962963,0.970492,0.922559,0.912052,0.989655,0.898026,0.98,0.976974,0.976109,0.944828,0.966443,0.906667,0.970297,0.983333,0.996622,0.965636]
predictive_accuracy
0.9525458509683211
prior_entropy
4.700438279892712
recall
0.9525458509683211 [0.98,0.916667,0.993333,0.93,0.9,0.956376,0.943333,0.963333,0.973333,0.966667,0.953333,0.986667,0.916388,0.933333,0.956667,0.91,0.98,0.99,0.953333,0.913333,0.96,0.906667,0.98,0.983333,0.983333,0.936667]
relative_absolute_error
0.06448001287640345
root_mean_prior_squared_error
0.19230768465256318
root_mean_squared_error
0.05278114281546227
root_relative_squared_error
0.2744619535658206
total_cost
0
area_under_roc_curve
0.9990940170940174 [0.997867,0.999422,0.999822,0.995822,0.999511,0.999956,0.999689,1,1,0.999956,0.999422,1,0.999467,0.999422,0.993733,0.998711,0.997333,0.999867,1,0.998933,0.999911,0.9988,1,0.999022,1,0.999778]
area_under_roc_curve
0.9980803418803419 [0.9984,0.998044,1,0.999556,0.998622,0.999778,0.998756,0.998,0.984222,0.999467,0.9996,1,0.997067,0.9976,1,0.986667,1,0.999511,1,0.999244,0.999378,0.9964,1,1,1,0.999778]
area_under_roc_curve
0.9988393162393162 [0.999822,0.999422,1,0.998622,0.999644,0.999378,0.998889,0.991067,0.9984,0.996044,0.999911,1,0.999822,0.9992,1,0.999867,0.999956,0.9992,0.997956,0.999289,1,0.999644,0.999778,0.998622,0.999911,0.995378]
area_under_roc_curve
0.9993367521367523 [0.999644,0.998933,0.999822,0.999556,0.999778,0.999867,0.999689,1,1,0.999156,1,0.999867,0.9984,0.999022,0.999956,0.992,1,1,0.999822,0.999111,1,0.998178,1,1,1,0.999956]
area_under_roc_curve
0.9979401709401711 [1,0.998711,1,0.999111,0.997867,0.998311,0.999067,0.997911,1,0.999511,0.999867,0.999911,0.998711,0.997822,1,0.999911,1,1,0.981867,0.987733,0.999289,0.997156,0.996267,0.999911,0.999911,0.9976]
area_under_roc_curve
0.9989623931623931 [1,0.9992,0.9924,0.992578,0.999778,0.998622,0.998178,1,1,0.999644,0.998756,1,0.999378,0.9996,0.999956,0.997422,0.999733,1,0.999956,0.999733,1,0.998889,1,1,1,0.9992]
area_under_roc_curve
0.9988974358974357 [0.999822,0.997911,1,0.998978,0.995289,0.9992,1,0.997022,1,0.999956,1,0.999867,0.998267,0.996044,0.999778,0.993333,0.999689,1,0.999778,0.999867,0.998267,0.999733,1,1,1,0.998533]
area_under_roc_curve
0.9988380022314733 [0.999911,0.99644,1,0.997063,0.998175,1,0.995639,1,0.999822,0.999866,0.999911,0.999911,0.999724,0.998932,0.998887,0.999822,0.999866,1,1,0.987672,0.999288,0.999243,0.999955,1,0.999866,0.999822]
area_under_roc_curve
0.9982330341467986 [0.999911,0.996929,1,0.994482,0.999199,0.99908,0.993591,1,0.999911,0.999822,0.999243,1,0.998754,1,1,0.998576,0.998843,0.999911,1,0.989497,0.997196,0.997819,0.996751,1,0.999911,0.99466]
area_under_roc_curve
0.9992204788241404 [1,0.997908,1,1,0.999466,0.994069,0.999288,1,1,0.999955,0.999777,0.999822,0.995238,0.99862,0.999777,0.999599,1,1,0.99951,1,0.999911,0.998487,0.999955,1,1,0.998175]
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
0.9462674743695005 [0.933333,0.896552,0.95082,0.892308,0.95082,0.966667,0.947368,0.983051,1,0.983051,0.90625,1,0.9,0.885246,0.965517,0.872727,0.966667,0.983607,0.983607,0.933333,0.949153,0.870968,0.983607,0.949153,1,0.949153]
f_measure
0.9452116437652915 [0.875,0.888889,1,0.95082,0.885246,0.9375,0.966667,0.947368,0.983051,0.952381,0.947368,0.983607,0.918033,0.903226,0.983051,0.813559,0.983051,0.983607,0.947368,0.947368,0.947368,0.9,0.983607,1,1,0.947368]
f_measure
0.9524607793666239 [0.967742,0.918033,0.983607,0.896552,0.903226,0.918033,0.947368,0.966667,0.931034,0.949153,0.966667,1,0.966667,0.933333,1,0.949153,0.983607,0.966667,0.933333,0.903226,1,0.9375,0.966667,0.983051,0.983607,0.909091]
f_measure
0.959987949764523 [0.935484,0.888889,0.983607,0.95082,0.933333,0.983607,0.952381,0.965517,0.983051,0.983051,1,0.966667,0.933333,0.949153,0.983607,0.881356,1,0.967742,0.983051,0.912281,0.983607,0.888889,1,0.983607,0.983051,0.983607]
f_measure
0.9448842537913962 [0.9375,0.885246,1,0.9375,0.896552,0.903226,0.966667,0.965517,0.983607,0.966667,0.947368,0.983607,0.896552,0.903226,1,0.966667,0.983051,1,0.915254,0.915254,0.95082,0.881356,0.915254,0.983051,0.983051,0.9]
f_measure
0.9666919059753138 [1,0.903226,0.983051,0.847458,0.933333,0.947368,0.983051,1,1,0.983051,0.95082,1,0.966667,0.966667,0.983051,0.885246,0.983051,1,0.983607,0.983607,1,0.915254,1,0.967742,1,0.967742]
f_measure
0.9470125333897145 [0.967742,0.903226,1,0.892857,0.793103,0.933333,0.952381,0.965517,0.967742,0.966667,0.983051,0.967742,0.9,0.933333,0.909091,0.9,0.966667,1,0.965517,0.967742,0.933333,0.9375,0.983607,0.983607,0.983051,0.965517]
f_measure
0.9537125460431052 [0.983607,0.875,1,0.949153,0.862069,0.983051,0.949153,1,0.966667,0.966667,0.95082,0.967742,0.949153,0.915254,0.949153,0.923077,0.983607,0.983051,1,0.877193,0.949153,0.912281,0.983607,0.983051,0.983051,0.95082]
f_measure
0.9488158970198964 [0.967742,0.870968,1,0.875,0.965517,0.949153,0.931034,1,0.966667,0.965517,0.965517,0.983051,0.896552,0.952381,1,0.892308,0.95082,0.966667,0.983051,0.851852,0.933333,0.903226,0.949153,1,0.983051,0.966667]
f_measure
0.9600846054965955 [0.966667,0.915254,0.967742,0.983607,0.949153,0.949153,0.947368,1,0.983051,0.983607,0.966667,0.933333,0.866667,0.885246,0.949153,0.95082,1,0.983607,0.949153,0.983607,0.983607,0.915254,0.983607,1,1,0.965517]
kappa
0.944
kappa
0.9426666666666667
kappa
0.9506666666666667
kappa
0.9586666666666667
kappa
0.9426666666666667
kappa
0.9653333333333334
kappa
0.9453333333333332
kappa
0.9519383857097075
kappa
0.9465982063441194
kappa
0.9586136099166925
kb_relative_information_score
0.9583259477211028
kb_relative_information_score
0.9515560383848056
kb_relative_information_score
0.9588629688164256
kb_relative_information_score
0.964395884840456
kb_relative_information_score
0.9504970296622054
kb_relative_information_score
0.964589863506285
kb_relative_information_score
0.9555118550202107
kb_relative_information_score
0.9610096837843123
kb_relative_information_score
0.9496142230660165
kb_relative_information_score
0.9633996697728594
mean_absolute_error
0.0050107040405738615
mean_absolute_error
0.005329447404185284
mean_absolute_error
0.004671554939534775
mean_absolute_error
0.004181661677465696
mean_absolute_error
0.005387078894384346
mean_absolute_error
0.004076207596028717
mean_absolute_error
0.004912458071125277
mean_absolute_error
0.0043736976722839995
mean_absolute_error
0.005451120735902236
mean_absolute_error
0.004298145567024529
mean_prior_absolute_error
0.07396449704142057
mean_prior_absolute_error
0.07396449704142057
mean_prior_absolute_error
0.07396449704142057
mean_prior_absolute_error
0.07396449704142057
mean_prior_absolute_error
0.07396449704142057
mean_prior_absolute_error
0.07396449704142057
mean_prior_absolute_error
0.07396449704142057
mean_prior_absolute_error
0.07396448587535052
mean_prior_absolute_error
0.07396447325283656
mean_prior_absolute_error
0.07396447325283656
number_of_instances
780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30]
number_of_instances
780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30]
number_of_instances
780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30]
number_of_instances
780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30]
number_of_instances
780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30]
number_of_instances
780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30]
number_of_instances
780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30]
number_of_instances
779 [30,30,30,30,30,30,30,30,30,30,30,30,29,30,30,30,30,30,30,30,30,30,30,30,30,30]
number_of_instances
779 [30,30,30,30,30,29,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30]
number_of_instances
779 [30,30,30,30,30,29,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30]
precision
0.9482902710797675 [0.933333,0.928571,0.935484,0.828571,0.935484,0.966667,1,1,1,1,0.852941,1,0.9,0.870968,1,0.96,0.966667,0.967742,0.967742,0.933333,0.965517,0.84375,0.967742,0.965517,1,0.965517]
precision
0.9479082388417925 [0.823529,0.848485,1,0.935484,0.870968,0.882353,0.966667,1,1,0.909091,1,0.967742,0.903226,0.875,1,0.827586,1,0.967742,1,1,1,0.9,0.967742,1,1,1]
precision
0.9539777686979644 [0.9375,0.903226,0.967742,0.928571,0.875,0.903226,1,0.966667,0.964286,0.965517,0.966667,1,0.966667,0.933333,1,0.965517,0.967742,0.966667,0.933333,0.875,1,0.882353,0.966667,1,0.967742,1]
precision
0.9616010193561638 [0.90625,0.848485,0.967742,0.935484,0.933333,0.967742,0.909091,1,1,1,1,0.966667,0.933333,0.965517,0.967742,0.896552,1,0.9375,1,0.962963,0.967742,1,1,0.967742,1,0.967742]
precision
0.9462861306069443 [0.882353,0.870968,1,0.882353,0.928571,0.875,0.966667,1,0.967742,0.966667,1,0.967742,0.928571,0.875,1,0.966667,1,1,0.931034,0.931034,0.935484,0.896552,0.931034,1,1,0.9]
precision
0.9673732922620575 [1,0.875,1,0.862069,0.933333,1,1,1,1,1,0.935484,1,0.966667,0.966667,1,0.870968,1,1,0.967742,0.967742,1,0.931034,1,0.9375,1,0.9375]
precision
0.9487780033667496 [0.9375,0.875,1,0.961538,0.821429,0.933333,0.909091,1,0.9375,0.966667,1,0.9375,0.9,0.933333,1,0.9,0.966667,1,1,0.9375,0.933333,0.882353,0.967742,0.967742,1,1]
precision
0.9551773114071416 [0.967742,0.823529,1,0.965517,0.892857,1,0.965517,1,0.966667,0.966667,0.935484,0.9375,0.933333,0.931034,0.965517,0.857143,0.967742,1,1,0.925926,0.965517,0.962963,0.967742,1,1,0.935484]
precision
0.9514193412138686 [0.9375,0.84375,1,0.823529,1,0.933333,0.964286,1,0.966667,1,1,1,0.928571,0.909091,1,0.828571,0.935484,0.966667,1,0.958333,0.933333,0.875,0.965517,1,1,0.966667]
precision
0.9606384905398142 [0.966667,0.931034,0.9375,0.967742,0.965517,0.933333,1,1,1,0.967742,0.966667,0.933333,0.866667,0.870968,0.965517,0.935484,1,0.967742,0.965517,0.967742,0.967742,0.931034,0.967742,1,1,1]
predictive_accuracy
0.9461538461538461
predictive_accuracy
0.9448717948717948
predictive_accuracy
0.9525641025641026
predictive_accuracy
0.9602564102564102
predictive_accuracy
0.9448717948717948
predictive_accuracy
0.9666666666666667
predictive_accuracy
0.9474358974358974
predictive_accuracy
0.9537869062901155
predictive_accuracy
0.9486521181001284
predictive_accuracy
0.9602053915275995
prior_entropy
4.700441149362989
prior_entropy
4.700441149362989
prior_entropy
4.700441149362989
prior_entropy
4.700441149362989
prior_entropy
4.700441149362989
prior_entropy
4.700441149362989
prior_entropy
4.700441149362989
prior_entropy
4.700435698259304
prior_entropy
4.700429514669705
prior_entropy
4.700429514669705
recall
0.9461538461538461 [0.933333,0.866667,0.966667,0.966667,0.966667,0.966667,0.9,0.966667,1,0.966667,0.966667,1,0.9,0.9,0.933333,0.8,0.966667,1,1,0.933333,0.933333,0.9,1,0.933333,1,0.933333]
recall
0.9448717948717948 [0.933333,0.933333,1,0.966667,0.9,1,0.966667,0.9,0.966667,1,0.9,1,0.933333,0.933333,0.966667,0.8,0.966667,1,0.9,0.9,0.9,0.9,1,1,1,0.9]
recall
0.9525641025641025 [1,0.933333,1,0.866667,0.933333,0.933333,0.9,0.966667,0.9,0.933333,0.966667,1,0.966667,0.933333,1,0.933333,1,0.966667,0.933333,0.933333,1,1,0.966667,0.966667,1,0.833333]
recall
0.9602564102564103 [0.966667,0.933333,1,0.966667,0.933333,1,1,0.933333,0.966667,0.966667,1,0.966667,0.933333,0.933333,1,0.866667,1,1,0.966667,0.866667,1,0.8,1,1,0.966667,1]
recall
0.9448717948717948 [1,0.9,1,1,0.866667,0.933333,0.966667,0.933333,1,0.966667,0.9,1,0.866667,0.933333,1,0.966667,0.966667,1,0.9,0.9,0.966667,0.866667,0.9,0.966667,0.966667,0.9]
recall
0.9666666666666667 [1,0.933333,0.966667,0.833333,0.933333,0.9,0.966667,1,1,0.966667,0.966667,1,0.966667,0.966667,0.966667,0.9,0.966667,1,1,1,1,0.9,1,1,1,1]
recall
0.9474358974358974 [1,0.933333,1,0.833333,0.766667,0.933333,1,0.933333,1,0.966667,0.966667,1,0.9,0.933333,0.833333,0.9,0.966667,1,0.933333,1,0.933333,1,1,1,0.966667,0.933333]
recall
0.9537869062901155 [1,0.933333,1,0.933333,0.833333,0.966667,0.933333,1,0.966667,0.966667,0.966667,1,0.965517,0.9,0.933333,1,1,0.966667,1,0.833333,0.933333,0.866667,1,0.966667,0.966667,0.966667]
recall
0.9486521181001284 [1,0.9,1,0.933333,0.933333,0.965517,0.9,1,0.966667,0.933333,0.933333,0.966667,0.866667,1,1,0.966667,0.966667,0.966667,0.966667,0.766667,0.933333,0.933333,0.933333,1,0.966667,0.966667]
recall
0.9602053915275995 [0.966667,0.9,1,1,0.933333,0.965517,0.9,1,0.966667,1,0.966667,0.933333,0.866667,0.9,0.933333,0.966667,1,1,0.933333,1,1,0.9,1,1,1,0.933333]
relative_absolute_error
0.0677447186285582
relative_absolute_error
0.07205412890458461
relative_absolute_error
0.06315942278250977
relative_absolute_error
0.05653606587933587
relative_absolute_error
0.07283330665207592
relative_absolute_error
0.05511032669830792
relative_absolute_error
0.06641643312161336
relative_absolute_error
0.05913240145621809
relative_absolute_error
0.07369917605264882
relative_absolute_error
0.05811094675591019
root_mean_prior_squared_error
0.19230769991209876
root_mean_prior_squared_error
0.19230769991209876
root_mean_prior_squared_error
0.19230769991209876
root_mean_prior_squared_error
0.19230769991209876
root_mean_prior_squared_error
0.19230769991209876
root_mean_prior_squared_error
0.19230769991209876
root_mean_prior_squared_error
0.19230769991209876
root_mean_prior_squared_error
0.19230767088031558
root_mean_prior_squared_error
0.19230763806177284
root_mean_prior_squared_error
0.19230763806177284
root_mean_squared_error
0.0528364865531693
root_mean_squared_error
0.057621169477297667
root_mean_squared_error
0.05124426078951404
root_mean_squared_error
0.048586216958312604
root_mean_squared_error
0.057917176608690654
root_mean_squared_error
0.04757237384769428
root_mean_squared_error
0.05341219234787121
root_mean_squared_error
0.05163842692021438
root_mean_squared_error
0.05649327271248823
root_mean_squared_error
0.04931029856817292
root_relative_squared_error
0.27474971921207597
root_relative_squared_error
0.2996300694337019
root_relative_squared_error
0.26647014556846704
root_relative_squared_error
0.25264831819277495
root_relative_squared_error
0.30116930645607953
root_relative_squared_error
0.24737633422602925
root_relative_squared_error
0.27774338922614744
root_relative_squared_error
0.2685198499042299
root_relative_squared_error
0.29376510096984043
root_relative_squared_error
0.25641362488334196
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
usercpu_time_millis
49693.07847300661
usercpu_time_millis
50435.67921700742
usercpu_time_millis
51942.11111799814
usercpu_time_millis
50741.53730100079
usercpu_time_millis
53630.23960300052
usercpu_time_millis
53378.05616998958
usercpu_time_millis
50576.6362669965
usercpu_time_millis
49948.2387839962
usercpu_time_millis
50421.0582079977
usercpu_time_millis
49929.63895700086
usercpu_time_millis_testing
61.42494500090834
usercpu_time_millis_testing
70.01284500438487
usercpu_time_millis_testing
72.71136499912245
usercpu_time_millis_testing
67.64019499678398
usercpu_time_millis_testing
68.09027700364823
usercpu_time_millis_testing
68.25024399586255
usercpu_time_millis_testing
65.86278399481671
usercpu_time_millis_testing
69.79230599972652
usercpu_time_millis_testing
65.20384299801663
usercpu_time_millis_testing
75.45042599667795
usercpu_time_millis_training
49631.6535280057
usercpu_time_millis_training
50365.666372003034
usercpu_time_millis_training
51869.399752999016
usercpu_time_millis_training
50673.897106004006
usercpu_time_millis_training
53562.14932599687
usercpu_time_millis_training
53309.805925993714
usercpu_time_millis_training
50510.773483001685
usercpu_time_millis_training
49878.44647799648
usercpu_time_millis_training
50355.85436499969
usercpu_time_millis_training
49854.18853100418
wall_clock_time_millis
49694.34642791748
wall_clock_time_millis
50438.57288360596
wall_clock_time_millis
51943.40252876282
wall_clock_time_millis
50791.73684120178
wall_clock_time_millis
53643.39733123779
wall_clock_time_millis
53395.851612091064
wall_clock_time_millis
50578.315019607544
wall_clock_time_millis
49949.37586784363
wall_clock_time_millis
50424.67641830444
wall_clock_time_millis
49946.59662246704
wall_clock_time_millis_testing
61.43307685852051
wall_clock_time_millis_testing
70.02115249633789
wall_clock_time_millis_testing
72.72005081176758
wall_clock_time_millis_testing
67.64912605285645
wall_clock_time_millis_testing
68.13287734985352
wall_clock_time_millis_testing
68.25828552246094
wall_clock_time_millis_testing
65.86980819702148
wall_clock_time_millis_testing
69.80133056640625
wall_clock_time_millis_testing
65.21224975585938
wall_clock_time_millis_testing
75.47926902770996
wall_clock_time_millis_training
49632.91335105896
wall_clock_time_millis_training
50368.55173110962
wall_clock_time_millis_training
51870.68247795105
wall_clock_time_millis_training
50724.087715148926
wall_clock_time_millis_training
53575.26445388794
wall_clock_time_millis_training
53327.5933265686
wall_clock_time_millis_training
50512.44521141052
wall_clock_time_millis_training
49879.57453727722
wall_clock_time_millis_training
50359.464168548584
wall_clock_time_millis_training
49871.11735343933