10588219
32117
VAIBHAV JAISWAL
18
Supervised Classification
19167
sklearn.pipeline.Pipeline(numerical=sklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,scaler=sklearn.preprocessing._data.StandardScaler),model=sklearn.ensemble._forest.RandomForestClassifier)(1)
8304105
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
bootstrap
true
19095
ccp_alpha
0.0
19095
class_weight
null
19095
criterion
"gini"
19095
max_depth
null
19095
max_features
"auto"
19095
max_leaf_nodes
null
19095
max_samples
null
19095
min_impurity_decrease
0.0
19095
min_samples_leaf
1
19095
min_samples_split
2
19095
min_weight_fraction_leaf
0.0
19095
n_estimators
100
19095
n_jobs
null
19095
oob_score
false
19095
random_state
0
19095
verbose
0
19095
warm_start
false
19095
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
19167
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"}}]
19167
verbose
false
19167
openml-python
Sklearn_1.0.2.
18
mfeat-morphological
https://www.openml.org/data/download/18/dataset_18_mfeat-morphological.arff
-1
22104005
description
https://api.openml.org/data/download/22104005/description.xml
-1
22104006
predictions
https://api.openml.org/data/download/22104006/predictions.arff
area_under_roc_curve
0.5080723611111112 [0.999743,0.362731,0.580451,0.679549,0.49301,0.382733,0.352926,0.42829,0.391518,0.409772]
average_cost
0
f_measure
0.12623571730778108 [0.98995,0.004866,0.113695,0.148883,0,0,0,0,0.004963,0]
kappa
0.02833333333333333
kb_relative_information_score
0.09998527186530887
mean_absolute_error
0.17375446666666233
mean_prior_absolute_error
0.18000000000000554
weighted_recall
0.1255 [0.985,0.005,0.11,0.15,0,0,0,0,0.005,0]
number_of_instances
2000 [200,200,200,200,200,200,200,200,200,200]
precision
0.12700452498718268 [0.994949,0.004739,0.117647,0.147783,0,0,0,0,0.004926,0]
predictive_accuracy
0.1255
prior_entropy
3.3219280948872383
relative_absolute_error
0.9653025925925387
root_mean_prior_squared_error
0.3000000000000046
root_mean_squared_error
0.3810950196055269
root_relative_squared_error
1.2703167320184037
total_cost
0
unweighted_recall
0.1255 [0.985,0.005,0.11,0.15,0,0,0,0,0.005,0]
area_under_roc_curve
0.5187361111111112 [0.999583,0.367778,0.587222,0.75625,0.499583,0.388472,0.363611,0.427778,0.416528,0.380556]
area_under_roc_curve
0.5079305555555556 [1,0.353194,0.628611,0.683056,0.515,0.363889,0.327778,0.425,0.368333,0.414444]
area_under_roc_curve
0.49958333333333343 [0.999444,0.315972,0.4925,0.690833,0.481667,0.425694,0.362917,0.446667,0.379861,0.400278]
area_under_roc_curve
0.5088194444444443 [1,0.369583,0.541667,0.716528,0.507222,0.35,0.362917,0.425,0.38,0.435278]
area_under_roc_curve
0.5133194444444444 [1,0.374444,0.597361,0.72875,0.48875,0.406806,0.319444,0.419444,0.382639,0.415556]
area_under_roc_curve
0.5109027777777778 [1,0.352222,0.654583,0.564444,0.580972,0.369444,0.355556,0.425,0.398472,0.408333]
area_under_roc_curve
0.5079583333333333 [0.998472,0.345972,0.644167,0.634861,0.497778,0.375,0.382917,0.416667,0.383056,0.400694]
area_under_roc_curve
0.5034166666666667 [1,0.377222,0.549028,0.663472,0.430278,0.372361,0.361111,0.438889,0.441806,0.4]
area_under_roc_curve
0.5175277777777777 [1,0.443472,0.615417,0.728611,0.454028,0.375694,0.325,0.433333,0.372361,0.427361]
area_under_roc_curve
0.4950833333333334 [1,0.325139,0.506806,0.637639,0.477083,0.399861,0.368056,0.425,0.395833,0.415417]
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
0.13312267535630823 [0.974359,0,0.210526,0.146341,0,0,0,0,0,0]
f_measure
0.11664266911005425 [0.97561,0,0.051282,0.139535,0,0,0,0,0,0]
f_measure
0.12172161172161172 [0.974359,0,0.1,0.142857,0,0,0,0,0,0]
f_measure
0.12642857142857142 [1,0,0.114286,0.15,0,0,0,0,0,0]
f_measure
0.13551282051282051 [1,0,0.15,0.205128,0,0,0,0,0,0]
f_measure
0.12127659574468085 [1,0,0.212766,0,0,0,0,0,0,0]
f_measure
0.11243589743589742 [0.974359,0,0,0.15,0,0,0,0,0,0]
f_measure
0.11552631578947369 [1,0,0.05,0.105263,0,0,0,0,0,0]
f_measure
0.13581252783526762 [1,0.04878,0.105263,0.204082,0,0,0,0,0,0]
f_measure
0.1381482322658793 [1,0,0.117647,0.216216,0,0,0,0,0.047619,0]
kappa
0.03333333333333333
kappa
0.02222222222222221
kappa
0.02222222222222221
kappa
0.02777777777777777
kappa
0.03888888888888889
kappa
0.02777777777777777
kappa
0.011111111111111105
kappa
0.016666666666666666
kappa
0.04444444444444445
kappa
0.03888888888888889
kb_relative_information_score
0.10188713152310011
kb_relative_information_score
0.10038782339001916
kb_relative_information_score
0.09015574439136018
kb_relative_information_score
0.09876935552157336
kb_relative_information_score
0.10775281032569663
kb_relative_information_score
0.09997457993196802
kb_relative_information_score
0.08420850440163383
kb_relative_information_score
0.09407246007550318
kb_relative_information_score
0.11652263126346254
kb_relative_information_score
0.10612167782873509
mean_absolute_error
0.17378999999999992
mean_absolute_error
0.1736299999999999
mean_absolute_error
0.17577999999999988
mean_absolute_error
0.1736866666666666
mean_absolute_error
0.17226499999999992
mean_absolute_error
0.17383966666666656
mean_absolute_error
0.17589749999999993
mean_absolute_error
0.17486999999999994
mean_absolute_error
0.17078999999999983
mean_absolute_error
0.1729958333333332
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
0.1365079365079365 [1,0,0.222222,0.142857,0,0,0,0,0,0]
precision
0.11354473139370165 [0.952381,0,0.052632,0.130435,0,0,0,0,0,0]
precision
0.12363636363636363 [1,0,0.1,0.136364,0,0,0,0,0,0]
precision
0.12833333333333333 [1,0,0.133333,0.15,0,0,0,0,0,0]
precision
0.13605263157894737 [1,0,0.15,0.210526,0,0,0,0,0,0]
precision
0.11851851851851851 [1,0,0.185185,0,0,0,0,0,0,0]
precision
0.115 [1,0,0,0.15,0,0,0,0,0,0]
precision
0.11611111111111111 [1,0,0.05,0.111111,0,0,0,0,0,0]
precision
0.13311439518336068 [1,0.047619,0.111111,0.172414,0,0,0,0,0,0]
precision
0.14236058059587473 [1,0,0.142857,0.235294,0,0,0,0,0.045455,0]
predictive_accuracy
0.13
predictive_accuracy
0.12
predictive_accuracy
0.12
predictive_accuracy
0.125
predictive_accuracy
0.135
predictive_accuracy
0.125
predictive_accuracy
0.11
predictive_accuracy
0.115
predictive_accuracy
0.14
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
0.9655000000000006
relative_absolute_error
0.9646111111111115
relative_absolute_error
0.9765555555555561
relative_absolute_error
0.9649259259259266
relative_absolute_error
0.9570277777777784
relative_absolute_error
0.9657759259259264
relative_absolute_error
0.977208333333334
relative_absolute_error
0.9715000000000008
relative_absolute_error
0.9488333333333334
relative_absolute_error
0.9610879629629633
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
0.38157050949194327
root_mean_squared_error
0.3803054008058341
root_mean_squared_error
0.3827557088861626
root_mean_squared_error
0.3814450206827735
root_mean_squared_error
0.3816681336433573
root_mean_squared_error
0.38055155861035556
root_mean_squared_error
0.38730958700293233
root_mean_squared_error
0.38022463707062365
root_mean_squared_error
0.37530211422262505
root_mean_squared_error
0.3797136168710592
root_relative_squared_error
1.2719016983064784
root_relative_squared_error
1.267684669352781
root_relative_squared_error
1.275852362953876
root_relative_squared_error
1.2714834022759123
root_relative_squared_error
1.2722271121445252
root_relative_squared_error
1.2685051953678528
root_relative_squared_error
1.291031956676442
root_relative_squared_error
1.2674154569020795
root_relative_squared_error
1.251007047408751
root_relative_squared_error
1.2657120562368647
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
0.12999999999999998 [0.95,0,0.2,0.15,0,0,0,0,0,0]
unweighted_recall
0.12 [1,0,0.05,0.15,0,0,0,0,0,0]
unweighted_recall
0.12 [0.95,0,0.1,0.15,0,0,0,0,0,0]
unweighted_recall
0.125 [1,0,0.1,0.15,0,0,0,0,0,0]
unweighted_recall
0.13499999999999998 [1,0,0.15,0.2,0,0,0,0,0,0]
unweighted_recall
0.125 [1,0,0.25,0,0,0,0,0,0,0]
unweighted_recall
0.10999999999999999 [0.95,0,0,0.15,0,0,0,0,0,0]
unweighted_recall
0.11500000000000002 [1,0,0.05,0.1,0,0,0,0,0,0]
unweighted_recall
0.14 [1,0.05,0.1,0.25,0,0,0,0,0,0]
unweighted_recall
0.135 [1,0,0.1,0.2,0,0,0,0,0.05,0]
usercpu_time_millis
406.25
usercpu_time_millis
359.375
usercpu_time_millis
359.375
usercpu_time_millis
359.375
usercpu_time_millis
390.625
usercpu_time_millis
359.375
usercpu_time_millis
359.375
usercpu_time_millis
375
usercpu_time_millis
359.375
usercpu_time_millis
375
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
15.625
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
15.625
usercpu_time_millis_training
390.625
usercpu_time_millis_training
343.75
usercpu_time_millis_training
343.75
usercpu_time_millis_training
343.75
usercpu_time_millis_training
375
usercpu_time_millis_training
343.75
usercpu_time_millis_training
343.75
usercpu_time_millis_training
359.375
usercpu_time_millis_training
343.75
usercpu_time_millis_training
359.375
wall_clock_time_millis
406.7685604095459
wall_clock_time_millis
368.76654624938965
wall_clock_time_millis
351.8202304840088
wall_clock_time_millis
357.79428482055664
wall_clock_time_millis
382.7798366546631
wall_clock_time_millis
355.79514503479004
wall_clock_time_millis
360.77094078063965
wall_clock_time_millis
363.8110160827637
wall_clock_time_millis
354.7952175140381
wall_clock_time_millis
372.7850914001465
wall_clock_time_millis_testing
18.98980140686035
wall_clock_time_millis_testing
16.99042320251465
wall_clock_time_millis_testing
16.988754272460938
wall_clock_time_millis_testing
16.99042320251465
wall_clock_time_millis_testing
16.989469528198242
wall_clock_time_millis_testing
16.989469528198242
wall_clock_time_millis_testing
16.990184783935547
wall_clock_time_millis_testing
16.990184783935547
wall_clock_time_millis_testing
16.99376106262207
wall_clock_time_millis_testing
16.990184783935547
wall_clock_time_millis_training
387.77875900268555
wall_clock_time_millis_training
351.776123046875
wall_clock_time_millis_training
334.83147621154785
wall_clock_time_millis_training
340.803861618042
wall_clock_time_millis_training
365.79036712646484
wall_clock_time_millis_training
338.8056755065918
wall_clock_time_millis_training
343.7807559967041
wall_clock_time_millis_training
346.8208312988281
wall_clock_time_millis_training
337.801456451416
wall_clock_time_millis_training
355.79490661621094
weighted_recall
0.13 [0.95,0,0.2,0.15,0,0,0,0,0,0]
weighted_recall
0.12 [1,0,0.05,0.15,0,0,0,0,0,0]
weighted_recall
0.12 [0.95,0,0.1,0.15,0,0,0,0,0,0]
weighted_recall
0.125 [1,0,0.1,0.15,0,0,0,0,0,0]
weighted_recall
0.135 [1,0,0.15,0.2,0,0,0,0,0,0]
weighted_recall
0.125 [1,0,0.25,0,0,0,0,0,0,0]
weighted_recall
0.11 [0.95,0,0,0.15,0,0,0,0,0,0]
weighted_recall
0.115 [1,0,0.05,0.1,0,0,0,0,0,0]
weighted_recall
0.14 [1,0.05,0.1,0.25,0,0,0,0,0,0]
weighted_recall
0.135 [1,0,0.1,0.2,0,0,0,0,0.05,0]