10588251
32117
VAIBHAV JAISWAL
18
Supervised Classification
19174
sklearn.pipeline.Pipeline(numerical=sklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,scaler=sklearn.preprocessing._data.StandardScaler),model=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(1)
8304109
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
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
19174
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"}}]
19174
verbose
false
19174
categorical_features
null
19175
early_stopping
"auto"
19175
l2_regularization
0.0
19175
learning_rate
0.1
19175
loss
"auto"
19175
max_bins
255
19175
max_depth
null
19175
max_iter
100
19175
max_leaf_nodes
31
19175
min_samples_leaf
20
19175
monotonic_cst
null
19175
n_iter_no_change
10
19175
random_state
0
19175
scoring
"loss"
19175
tol
1e-07
19175
validation_fraction
0.1
19175
verbose
0
19175
warm_start
false
19175
openml-python
Sklearn_1.0.2.
18
mfeat-morphological
https://www.openml.org/data/download/18/dataset_18_mfeat-morphological.arff
-1
22104069
description
https://api.openml.org/data/download/22104069/description.xml
-1
22104070
predictions
https://api.openml.org/data/download/22104070/predictions.arff
area_under_roc_curve
0.5353144444444444 [0.99915,0.307214,0.707519,0.690971,0.587286,0.386454,0.535971,0.343853,0.161283,0.633443]
average_cost
0
f_measure
0.12782146671658295 [0.98995,0.009877,0.096692,0.151515,0.020305,0,0,0,0.009877,0]
kappa
0.029999999999999995
kb_relative_information_score
0.09179512135030095
mean_absolute_error
0.1744223152200107
mean_prior_absolute_error
0.18000000000000554
weighted_recall
0.127 [0.985,0.01,0.095,0.15,0.02,0,0,0,0.01,0]
number_of_instances
2000 [200,200,200,200,200,200,200,200,200,200]
precision
0.12865870671171953 [0.994949,0.009756,0.098446,0.153061,0.020619,0,0,0,0.009756,0]
predictive_accuracy
0.127
prior_entropy
3.3219280948872383
relative_absolute_error
0.9690128623333629
root_mean_prior_squared_error
0.3000000000000046
root_mean_squared_error
0.40142129792555986
root_relative_squared_error
1.338070993085179
total_cost
0
unweighted_recall
0.127 [0.985,0.01,0.095,0.15,0.02,0,0,0,0.01,0]
area_under_roc_curve
0.5305277777777778 [0.999167,0.329167,0.671944,0.761111,0.553889,0.329722,0.5875,0.368611,0.098889,0.605278]
area_under_roc_curve
0.5336666666666667 [1,0.296944,0.759722,0.674722,0.625833,0.395833,0.517083,0.350278,0.101944,0.614306]
area_under_roc_curve
0.5414166666666667 [0.997222,0.265833,0.632222,0.705556,0.596667,0.4775,0.523194,0.412222,0.142222,0.661528]
area_under_roc_curve
0.5230833333333333 [1,0.314444,0.674167,0.715972,0.555556,0.414306,0.46375,0.290833,0.167222,0.634583]
area_under_roc_curve
0.5403611111111111 [1,0.316389,0.701944,0.736667,0.633611,0.421389,0.533889,0.365,0.096111,0.598611]
area_under_roc_curve
0.5278611111111111 [1,0.264444,0.755556,0.525556,0.622778,0.348611,0.567639,0.305,0.228056,0.660972]
area_under_roc_curve
0.5155555555555555 [0.998611,0.280556,0.693056,0.633056,0.602778,0.291389,0.580139,0.337222,0.118611,0.620139]
area_under_roc_curve
0.5437500000000001 [1,0.326667,0.706111,0.725278,0.585,0.404722,0.479306,0.3075,0.262778,0.640139]
area_under_roc_curve
0.5369999999999999 [1,0.372778,0.704722,0.715833,0.554722,0.426389,0.492778,0.326389,0.16,0.616389]
area_under_roc_curve
0.5481666666666666 [1,0.310278,0.746111,0.7075,0.545,0.333889,0.589861,0.357778,0.222778,0.668472]
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
0.14294871794871794 [0.974359,0,0.205128,0.25,0,0,0,0,0,0]
f_measure
0.1178433889602054 [0.97561,0,0.105263,0.097561,0,0,0,0,0,0]
f_measure
0.12637159588379102 [0.974359,0,0.045455,0.243902,0,0,0,0,0,0]
f_measure
0.12612246392734197 [1,0,0.055556,0.108108,0.097561,0,0,0,0,0]
f_measure
0.1346282372598162 [1,0,0.055556,0.238095,0.052632,0,0,0,0,0]
f_measure
0.12907268170426067 [1,0,0.238095,0,0.052632,0,0,0,0,0]
f_measure
0.10769230769230768 [0.974359,0,0,0.102564,0,0,0,0,0,0]
f_measure
0.12640763031006932 [1,0.04878,0.045455,0.114286,0,0,0,0,0.055556,0]
f_measure
0.1314227642276423 [1,0.05,0.097561,0.166667,0,0,0,0,0,0]
f_measure
0.13146434960388448 [1,0,0.114286,0.153846,0,0,0,0,0.046512,0]
kappa
0.04444444444444445
kappa
0.02222222222222221
kappa
0.02777777777777777
kappa
0.02777777777777777
kappa
0.03888888888888889
kappa
0.03333333333333333
kappa
0.005555555555555545
kappa
0.02777777777777777
kappa
0.03888888888888889
kappa
0.03333333333333333
kb_relative_information_score
0.10085470487601661
kb_relative_information_score
0.09133677492496128
kb_relative_information_score
0.08404705174750551
kb_relative_information_score
0.08772565959592324
kb_relative_information_score
0.1006985675526039
kb_relative_information_score
0.09315259102684069
kb_relative_information_score
0.06920858673578743
kb_relative_information_score
0.08779485238955305
kb_relative_information_score
0.1047070279482166
kb_relative_information_score
0.09842539670556763
mean_absolute_error
0.17281448647383407
mean_absolute_error
0.1747298451843104
mean_absolute_error
0.17591452710360894
mean_absolute_error
0.17480155609683531
mean_absolute_error
0.17284754948107497
mean_absolute_error
0.17422646501154396
mean_absolute_error
0.17819350569494755
mean_absolute_error
0.17547390606365845
mean_absolute_error
0.17183679620014178
mean_absolute_error
0.1733845148901528
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
precision
0.14605263157894735 [1,0,0.210526,0.25,0,0,0,0,0,0]
precision
0.11587301587301586 [0.952381,0,0.111111,0.095238,0,0,0,0,0,0]
precision
0.12797619047619047 [1,0,0.041667,0.238095,0,0,0,0,0,0]
precision
0.12753851540616246 [1,0,0.0625,0.117647,0.095238,0,0,0,0,0]
precision
0.13453282828282828 [1,0,0.0625,0.227273,0.055556,0,0,0,0,0]
precision
0.12828282828282828 [1,0,0.227273,0,0.055556,0,0,0,0,0]
precision
0.11052631578947368 [1,0,0,0.105263,0,0,0,0,0,0]
precision
0.12851190476190477 [1,0.047619,0.041667,0.133333,0,0,0,0,0.0625,0]
precision
0.12880952380952382 [1,0.05,0.095238,0.142857,0,0,0,0,0,0]
precision
0.13347063310450039 [1,0,0.133333,0.157895,0,0,0,0,0.043478,0]
predictive_accuracy
0.14
predictive_accuracy
0.12
predictive_accuracy
0.125
predictive_accuracy
0.125
predictive_accuracy
0.135
predictive_accuracy
0.13
predictive_accuracy
0.105
predictive_accuracy
0.125
predictive_accuracy
0.135
predictive_accuracy
0.13
prior_entropy
3.321928094887355
prior_entropy
3.321928094887355
prior_entropy
3.321928094887355
prior_entropy
3.321928094887355
prior_entropy
3.321928094887355
prior_entropy
3.321928094887355
prior_entropy
3.321928094887355
prior_entropy
3.321928094887355
prior_entropy
3.321928094887355
prior_entropy
3.321928094887355
relative_absolute_error
0.9600804804101903
relative_absolute_error
0.9707213621350589
relative_absolute_error
0.9773029283533841
relative_absolute_error
0.9711197560935306
relative_absolute_error
0.9602641637837509
relative_absolute_error
0.9679248056196897
relative_absolute_error
0.9899639205274875
relative_absolute_error
0.9748550336869924
relative_absolute_error
0.9546488677785665
relative_absolute_error
0.9632473049452944
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_squared_error
0.3999703539085684
root_mean_squared_error
0.4013732114243645
root_mean_squared_error
0.4042772091721088
root_mean_squared_error
0.4025365554729897
root_mean_squared_error
0.40061656218271097
root_mean_squared_error
0.399541974656886
root_mean_squared_error
0.40728419962962115
root_mean_squared_error
0.3994406604263493
root_mean_squared_error
0.3975671163273777
root_mean_squared_error
0.4015193808735094
root_relative_squared_error
1.3332345130285619
root_relative_squared_error
1.3379107047478822
root_relative_squared_error
1.3475906972403633
root_relative_squared_error
1.3417885182432996
root_relative_squared_error
1.3353885406090373
root_relative_squared_error
1.331806582189621
root_relative_squared_error
1.3576139987654046
root_relative_squared_error
1.3314688680878317
root_relative_squared_error
1.3252237210912596
root_relative_squared_error
1.3383979362450322
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
0.13999999999999999 [0.95,0,0.2,0.25,0,0,0,0,0,0]
unweighted_recall
0.12000000000000002 [1,0,0.1,0.1,0,0,0,0,0,0]
unweighted_recall
0.125 [0.95,0,0.05,0.25,0,0,0,0,0,0]
unweighted_recall
0.12500000000000003 [1,0,0.05,0.1,0.1,0,0,0,0,0]
unweighted_recall
0.135 [1,0,0.05,0.25,0.05,0,0,0,0,0]
unweighted_recall
0.13 [1,0,0.25,0,0.05,0,0,0,0,0]
unweighted_recall
0.10500000000000001 [0.95,0,0,0.1,0,0,0,0,0,0]
unweighted_recall
0.12500000000000003 [1,0.05,0.05,0.1,0,0,0,0,0.05,0]
unweighted_recall
0.135 [1,0.05,0.1,0.2,0,0,0,0,0,0]
unweighted_recall
0.13 [1,0,0.1,0.15,0,0,0,0,0.05,0]
usercpu_time_millis
34718.75
usercpu_time_millis
34828.125
usercpu_time_millis
34828.125
usercpu_time_millis
35406.25
usercpu_time_millis
35781.25
usercpu_time_millis
35812.5
usercpu_time_millis
35328.125
usercpu_time_millis
34953.125
usercpu_time_millis
35218.75
usercpu_time_millis
35515.625
usercpu_time_millis_testing
187.5
usercpu_time_millis_testing
187.5
usercpu_time_millis_testing
187.5
usercpu_time_millis_testing
187.5
usercpu_time_millis_testing
187.5
usercpu_time_millis_testing
187.5
usercpu_time_millis_testing
125
usercpu_time_millis_testing
187.5
usercpu_time_millis_testing
187.5
usercpu_time_millis_testing
187.5
usercpu_time_millis_training
34531.25
usercpu_time_millis_training
34640.625
usercpu_time_millis_training
34640.625
usercpu_time_millis_training
35218.75
usercpu_time_millis_training
35593.75
usercpu_time_millis_training
35625
usercpu_time_millis_training
35203.125
usercpu_time_millis_training
34765.625
usercpu_time_millis_training
35031.25
usercpu_time_millis_training
35328.125
wall_clock_time_millis
9112.754583358765
wall_clock_time_millis
9144.757509231567
wall_clock_time_millis
9300.668239593506
wall_clock_time_millis
9143.758296966553
wall_clock_time_millis
9172.741889953613
wall_clock_time_millis
9209.720134735107
wall_clock_time_millis
9197.728633880615
wall_clock_time_millis
9231.709241867065
wall_clock_time_millis
9158.750057220459
wall_clock_time_millis
9159.749984741211
wall_clock_time_millis_testing
48.970937728881836
wall_clock_time_millis_testing
50.971269607543945
wall_clock_time_millis_testing
51.97024345397949
wall_clock_time_millis_testing
48.97141456604004
wall_clock_time_millis_testing
49.97134208679199
wall_clock_time_millis_testing
51.969289779663086
wall_clock_time_millis_testing
69.95749473571777
wall_clock_time_millis_testing
49.97134208679199
wall_clock_time_millis_testing
49.971580505371094
wall_clock_time_millis_testing
49.971580505371094
wall_clock_time_millis_training
9063.783645629883
wall_clock_time_millis_training
9093.786239624023
wall_clock_time_millis_training
9248.697996139526
wall_clock_time_millis_training
9094.786882400513
wall_clock_time_millis_training
9122.770547866821
wall_clock_time_millis_training
9157.750844955444
wall_clock_time_millis_training
9127.771139144897
wall_clock_time_millis_training
9181.737899780273
wall_clock_time_millis_training
9108.778476715088
wall_clock_time_millis_training
9109.77840423584
weighted_recall
0.14 [0.95,0,0.2,0.25,0,0,0,0,0,0]
weighted_recall
0.12 [1,0,0.1,0.1,0,0,0,0,0,0]
weighted_recall
0.125 [0.95,0,0.05,0.25,0,0,0,0,0,0]
weighted_recall
0.125 [1,0,0.05,0.1,0.1,0,0,0,0,0]
weighted_recall
0.135 [1,0,0.05,0.25,0.05,0,0,0,0,0]
weighted_recall
0.13 [1,0,0.25,0,0.05,0,0,0,0,0]
weighted_recall
0.105 [0.95,0,0,0.1,0,0,0,0,0,0]
weighted_recall
0.125 [1,0.05,0.05,0.1,0,0,0,0,0.05,0]
weighted_recall
0.135 [1,0.05,0.1,0.2,0,0,0,0,0,0]
weighted_recall
0.13 [1,0,0.1,0.15,0,0,0,0,0.05,0]