10588193
32117
VAIBHAV JAISWAL
18
Supervised Classification
19162
sklearn.pipeline.Pipeline(numerical=sklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,scaler=sklearn.preprocessing._data.StandardScaler),model=sklearn.tree._classes.DecisionTreeClassifier)(1)
8304103
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
ccp_alpha
0.0
19085
class_weight
null
19085
criterion
"gini"
19085
max_depth
null
19085
max_features
null
19085
max_leaf_nodes
null
19085
min_impurity_decrease
0.0
19085
min_samples_leaf
1
19085
min_samples_split
2
19085
min_weight_fraction_leaf
0.0
19085
random_state
0
19085
splitter
"best"
19085
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
19162
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"}}]
19162
verbose
false
19162
openml-python
Sklearn_1.0.2.
18
mfeat-morphological
https://www.openml.org/data/download/18/dataset_18_mfeat-morphological.arff
-1
22103953
description
https://api.openml.org/data/download/22103953/description.xml
-1
22103954
predictions
https://api.openml.org/data/download/22103954/predictions.arff
area_under_roc_curve
0.5156752777777779 [0.991389,0.4575,0.494722,0.545833,0.460833,0.434722,0.443889,0.444722,0.437586,0.445556]
average_cost
0
f_measure
0.130967882346316 [0.982544,0.029056,0.090226,0.182278,0.025575,0,0,0,0,0]
kappa
0.034444444444444444
kb_relative_information_score
0.09198146819767429
mean_absolute_error
0.17369999999999444
mean_prior_absolute_error
0.18000000000000554
weighted_recall
0.131 [0.985,0.03,0.09,0.18,0.025,0,0,0,0,0]
number_of_instances
2000 [200,200,200,200,200,200,200,200,200,200]
precision
0.13095141729651905 [0.9801,0.028169,0.090452,0.184615,0.026178,0,0,0,0,0]
predictive_accuracy
0.131
prior_entropy
3.3219280948872383
relative_absolute_error
0.9649999999999394
root_mean_prior_squared_error
0.3000000000000046
root_mean_squared_error
0.41456134782575393
root_relative_squared_error
1.3818711594191586
total_cost
0
unweighted_recall
0.13099999999999998 [0.985,0.03,0.09,0.18,0.025,0,0,0,0,0]
area_under_roc_curve
0.52 [0.972222,0.461111,0.547222,0.583333,0.436111,0.444444,0.433333,0.444444,0.427778,0.45]
area_under_roc_curve
0.5138888888888888 [0.997222,0.466667,0.488889,0.547222,0.444444,0.425,0.45,0.444444,0.436111,0.438889]
area_under_roc_curve
0.5094444444444445 [0.969444,0.430556,0.425,0.575,0.469444,0.45,0.458333,0.444444,0.422222,0.45]
area_under_roc_curve
0.5225 [1,0.458333,0.488889,0.586111,0.508333,0.430556,0.444444,0.444444,0.427778,0.436111]
area_under_roc_curve
0.5230555555555555 [1,0.45,0.5,0.605556,0.475,0.425,0.441667,0.444444,0.444444,0.444444]
area_under_roc_curve
0.5119444444444443 [1,0.463889,0.508333,0.463889,0.480556,0.447222,0.447222,0.441667,0.419444,0.447222]
area_under_roc_curve
0.5038888888888888 [0.975,0.447222,0.455556,0.505556,0.455556,0.436111,0.433333,0.444444,0.441667,0.444444]
area_under_roc_curve
0.5066666666666666 [1,0.475,0.491667,0.458333,0.438889,0.425,0.438889,0.444444,0.447222,0.447222]
area_under_roc_curve
0.5233333333333333 [1,0.472222,0.519444,0.563889,0.458333,0.436111,0.455556,0.444444,0.433333,0.45]
area_under_roc_curve
0.5219722222222222 [1,0.45,0.522222,0.569444,0.441667,0.427778,0.436111,0.45,0.475278,0.447222]
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
0.14272727272727273 [0.95,0.045455,0.181818,0.25,0,0,0,0,0,0]
f_measure
0.12680988447562802 [0.97561,0.047619,0.058824,0.186047,0,0,0,0,0,0]
f_measure
0.11593874078275666 [0.926829,0,0,0.232558,0,0,0,0,0,0]
f_measure
0.14428933602901062 [1,0,0.058824,0.25641,0.12766,0,0,0,0,0]
f_measure
0.14369963369963368 [1,0,0.1,0.285714,0.051282,0,0,0,0,0]
f_measure
0.12282252564291159 [1,0.046512,0.12766,0,0.054054,0,0,0,0,0]
f_measure
0.11204384587843233 [0.974359,0.040816,0,0.105263,0,0,0,0,0,0]
f_measure
0.11443053070960048 [1,0.051282,0.093023,0,0,0,0,0,0,0]
f_measure
0.14023008411677387 [1,0.05,0.139535,0.212766,0,0,0,0,0,0]
f_measure
0.13714285714285715 [1,0,0.142857,0.228571,0,0,0,0,0,0]
kappa
0.04444444444444445
kappa
0.03333333333333333
kappa
0.02222222222222221
kappa
0.04999999999999998
kappa
0.04999999999999998
kappa
0.02777777777777777
kappa
0.011111111111111105
kappa
0.016666666666666666
kappa
0.04999999999999998
kappa
0.03888888888888889
kb_relative_information_score
0.10064855811782036
kb_relative_information_score
0.09019098321221325
kb_relative_information_score
0.07973340830660586
kb_relative_information_score
0.10587734557062371
kb_relative_information_score
0.10587734557062371
kb_relative_information_score
0.08496219575940964
kb_relative_information_score
0.06927583340099872
kb_relative_information_score
0.07450462085380237
kb_relative_information_score
0.10587734557062375
kb_relative_information_score
0.10286704561398392
mean_absolute_error
0.17199999999999974
mean_absolute_error
0.17399999999999977
mean_absolute_error
0.1759999999999998
mean_absolute_error
0.17099999999999974
mean_absolute_error
0.17099999999999974
mean_absolute_error
0.1749999999999998
mean_absolute_error
0.17799999999999983
mean_absolute_error
0.17699999999999982
mean_absolute_error
0.17099999999999974
mean_absolute_error
0.1719999999999998
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
0.14724358974358975 [0.95,0.041667,0.230769,0.25,0,0,0,0,0,0]
precision
0.12431771127423302 [0.952381,0.045455,0.071429,0.173913,0,0,0,0,0,0]
precision
0.1122153209109731 [0.904762,0,0,0.217391,0,0,0,0,0,0]
precision
0.14456975772765246 [1,0,0.071429,0.263158,0.111111,0,0,0,0,0]
precision
0.14253588516746413 [1,0,0.1,0.272727,0.052632,0,0,0,0,0]
precision
0.12134129013924409 [1,0.043478,0.111111,0,0.058824,0,0,0,0,0]
precision
0.11455938697318008 [1,0.034483,0,0.111111,0,0,0,0,0,0]
precision
0.1139588100686499 [1,0.052632,0.086957,0,0,0,0,0,0,0]
precision
0.13656199677938807 [1,0.05,0.130435,0.185185,0,0,0,0,0,0]
precision
0.1403030303030303 [1,0,0.136364,0.266667,0,0,0,0,0,0]
predictive_accuracy
0.14
predictive_accuracy
0.13
predictive_accuracy
0.12
predictive_accuracy
0.145
predictive_accuracy
0.145
predictive_accuracy
0.125
predictive_accuracy
0.11
predictive_accuracy
0.115
predictive_accuracy
0.145
predictive_accuracy
0.135
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
0.9555555555555552
relative_absolute_error
0.9666666666666665
relative_absolute_error
0.9777777777777777
relative_absolute_error
0.9499999999999996
relative_absolute_error
0.9499999999999996
relative_absolute_error
0.9722222222222221
relative_absolute_error
0.988888888888889
relative_absolute_error
0.9833333333333334
relative_absolute_error
0.9499999999999996
relative_absolute_error
0.9555555555555554
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
0.4123442466893136
root_mean_squared_error
0.41412558481697265
root_mean_squared_error
0.4177319714841081
root_mean_squared_error
0.41082572677204315
root_mean_squared_error
0.41140004861448387
root_mean_squared_error
0.4162331077653479
root_mean_squared_error
0.42015208886518407
root_mean_squared_error
0.41892720131306793
root_mean_squared_error
0.41170377700477767
root_mean_squared_error
0.4120409904096648
root_relative_squared_error
1.3744808222977127
root_relative_squared_error
1.3804186160565763
root_relative_squared_error
1.3924399049470282
root_relative_squared_error
1.3694190892401448
root_relative_squared_error
1.3713334953816139
root_relative_squared_error
1.3874436925511602
root_relative_squared_error
1.400506962883948
root_relative_squared_error
1.3964240043768938
root_relative_squared_error
1.3723459233492596
root_relative_squared_error
1.3734699680322169
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 [0.95,0.05,0.15,0.25,0,0,0,0,0,0]
unweighted_recall
0.13 [1,0.05,0.05,0.2,0,0,0,0,0,0]
unweighted_recall
0.12 [0.95,0,0,0.25,0,0,0,0,0,0]
unweighted_recall
0.145 [1,0,0.05,0.25,0.15,0,0,0,0,0]
unweighted_recall
0.14500000000000002 [1,0,0.1,0.3,0.05,0,0,0,0,0]
unweighted_recall
0.125 [1,0.05,0.15,0,0.05,0,0,0,0,0]
unweighted_recall
0.11000000000000001 [0.95,0.05,0,0.1,0,0,0,0,0,0]
unweighted_recall
0.11500000000000002 [1,0.05,0.1,0,0,0,0,0,0,0]
unweighted_recall
0.145 [1,0.05,0.15,0.25,0,0,0,0,0,0]
unweighted_recall
0.13499999999999998 [1,0,0.15,0.2,0,0,0,0,0,0]
usercpu_time_millis
15.625
usercpu_time_millis
15.625
usercpu_time_millis
15.625
usercpu_time_millis
0
usercpu_time_millis
15.625
usercpu_time_millis
15.625
usercpu_time_millis
0
usercpu_time_millis
0
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
0
usercpu_time_millis_testing
0
usercpu_time_millis_testing
0
usercpu_time_millis_testing
0
usercpu_time_millis_testing
0
usercpu_time_millis_testing
0
usercpu_time_millis_testing
0
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
15.625
usercpu_time_millis_training
15.625
usercpu_time_millis_training
0
usercpu_time_millis_training
0
usercpu_time_millis_training
15.625
usercpu_time_millis_training
15.625
wall_clock_time_millis
10.991096496582031
wall_clock_time_millis
9.99140739440918
wall_clock_time_millis
10.991811752319336
wall_clock_time_millis
8.992910385131836
wall_clock_time_millis
9.99307632446289
wall_clock_time_millis
10.970115661621094
wall_clock_time_millis
13.012170791625977
wall_clock_time_millis
10.988950729370117
wall_clock_time_millis
10.993003845214844
wall_clock_time_millis
9.993553161621094
wall_clock_time_millis_testing
0
wall_clock_time_millis_testing
0
wall_clock_time_millis_testing
0.9984970092773438
wall_clock_time_millis_testing
0
wall_clock_time_millis_testing
0
wall_clock_time_millis_testing
0.9996891021728516
wall_clock_time_millis_testing
0.9999275207519531
wall_clock_time_millis_testing
0
wall_clock_time_millis_testing
1.0006427764892578
wall_clock_time_millis_testing
0
wall_clock_time_millis_training
10.991096496582031
wall_clock_time_millis_training
9.99140739440918
wall_clock_time_millis_training
9.993314743041992
wall_clock_time_millis_training
8.992910385131836
wall_clock_time_millis_training
9.99307632446289
wall_clock_time_millis_training
9.970426559448242
wall_clock_time_millis_training
12.012243270874023
wall_clock_time_millis_training
10.988950729370117
wall_clock_time_millis_training
9.992361068725586
wall_clock_time_millis_training
9.993553161621094
weighted_recall
0.14 [0.95,0.05,0.15,0.25,0,0,0,0,0,0]
weighted_recall
0.13 [1,0.05,0.05,0.2,0,0,0,0,0,0]
weighted_recall
0.12 [0.95,0,0,0.25,0,0,0,0,0,0]
weighted_recall
0.145 [1,0,0.05,0.25,0.15,0,0,0,0,0]
weighted_recall
0.145 [1,0,0.1,0.3,0.05,0,0,0,0,0]
weighted_recall
0.125 [1,0.05,0.15,0,0.05,0,0,0,0,0]
weighted_recall
0.11 [0.95,0.05,0,0.1,0,0,0,0,0,0]
weighted_recall
0.115 [1,0.05,0.1,0,0,0,0,0,0,0]
weighted_recall
0.145 [1,0.05,0.15,0.25,0,0,0,0,0,0]
weighted_recall
0.135 [1,0,0.15,0.2,0,0,0,0,0,0]