10588178
32117
VAIBHAV JAISWAL
18
Supervised Classification
19159
sklearn.pipeline.Pipeline(numerical=sklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,scaler=sklearn.preprocessing._data.StandardScaler),model=sklearn.linear_model._stochastic_gradient.SGDClassifier)(1)
8304102
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
19159
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"}}]
19159
verbose
false
19159
alpha
0.0001
19160
average
false
19160
class_weight
null
19160
early_stopping
false
19160
epsilon
0.1
19160
eta0
0.0
19160
fit_intercept
true
19160
l1_ratio
0.15
19160
learning_rate
"optimal"
19160
loss
"hinge"
19160
max_iter
1000
19160
n_iter_no_change
5
19160
n_jobs
null
19160
penalty
"l2"
19160
power_t
0.5
19160
random_state
0
19160
shuffle
true
19160
tol
0.001
19160
validation_fraction
0.1
19160
verbose
0
19160
warm_start
false
19160
openml-python
Sklearn_1.0.2.
18
mfeat-morphological
https://www.openml.org/data/download/18/dataset_18_mfeat-morphological.arff
-1
22103923
description
https://api.openml.org/data/download/22103923/description.xml
-1
22103924
predictions
https://api.openml.org/data/download/22103924/predictions.arff
area_under_roc_curve
0.5155555555555555 [0.9925,0.444722,0.508611,0.539444,0.455278,0.4375,0.451667,0.442222,0.433056,0.450556]
average_cost
0
f_measure
0.1309826604879671 [0.992443,0.00489,0.10585,0.168478,0.015345,0.008989,0,0,0.008677,0.005155]
kappa
0.031111111111111107
kb_relative_information_score
0.08809946823109545
mean_absolute_error
0.17439999999999437
mean_prior_absolute_error
0.18000000000000554
weighted_recall
0.128 [0.985,0.005,0.095,0.155,0.015,0.01,0,0,0.01,0.005]
number_of_instances
2000 [200,200,200,200,200,200,200,200,200,200]
precision
0.13456574096389942 [1,0.004785,0.119497,0.184524,0.015707,0.008163,0,0,0.007663,0.005319]
predictive_accuracy
0.128
prior_entropy
3.3219280948872383
relative_absolute_error
0.9688888888888277
root_mean_prior_squared_error
0.3000000000000046
root_mean_squared_error
0.41761226035641524
root_relative_squared_error
1.3920408678546963
total_cost
0
unweighted_recall
0.12799999999999997 [0.985,0.005,0.095,0.155,0.015,0.01,0,0,0.01,0.005]
area_under_roc_curve
0.5194444444444444 [0.975,0.461111,0.561111,0.555556,0.441667,0.380556,0.438889,0.444444,0.494444,0.441667]
area_under_roc_curve
0.5138888888888887 [1,0.441667,0.488889,0.555556,0.461111,0.477778,0.436111,0.438889,0.397222,0.441667]
area_under_roc_curve
0.5083333333333333 [0.975,0.430556,0.444444,0.533333,0.483333,0.483333,0.455556,0.444444,0.394444,0.438889]
area_under_roc_curve
0.5138888888888888 [1,0.45,0.497222,0.480556,0.472222,0.475,0.461111,0.438889,0.419444,0.444444]
area_under_roc_curve
0.525 [1,0.494444,0.6,0.511111,0.433333,0.397222,0.45,0.438889,0.472222,0.452778]
area_under_roc_curve
0.5111111111111112 [1,0.455556,0.513889,0.486111,0.463889,0.386111,0.444444,0.441667,0.463889,0.455556]
area_under_roc_curve
0.5055555555555555 [0.975,0.447222,0.436111,0.533333,0.458333,0.380556,0.438889,0.444444,0.488889,0.452778]
area_under_roc_curve
0.5111111111111111 [1,0.444444,0.491667,0.525,0.427778,0.511111,0.444444,0.447222,0.366667,0.452778]
area_under_roc_curve
0.5388888888888889 [1,0.436111,0.536111,0.694444,0.452778,0.497222,0.463889,0.444444,0.388889,0.475]
area_under_roc_curve
0.5083333333333333 [1,0.386111,0.516667,0.519444,0.458333,0.386111,0.483333,0.438889,0.444444,0.45]
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
0.1416041948918661 [0.974359,0,0.214286,0.2,0,0.027397,0,0,0,0]
f_measure
0.12298507462686567 [1,0,0,0.2,0,0,0,0,0.029851,0]
f_measure
0.11722537112010796 [0.974359,0,0.04,0.157895,0,0,0,0,0,0]
f_measure
0.12324684881710578 [1,0,0.064516,0.054054,0.08,0,0,0,0.033898,0]
f_measure
0.137037037037037 [1,0,0.259259,0.111111,0,0,0,0,0,0]
f_measure
0.11904761904761903 [1,0,0.133333,0.057143,0,0,0,0,0,0]
f_measure
0.11616605616605616 [0.974359,0,0,0.142857,0.044444,0,0,0,0,0]
f_measure
0.1223264540337711 [1,0,0,0.146341,0,0.076923,0,0,0,0]
f_measure
0.1637166048486803 [1,0.037736,0.148148,0.4,0,0,0,0,0,0.051282]
f_measure
0.12046035805626598 [1,0,0.117647,0.086957,0,0,0,0,0,0]
kappa
0.03888888888888889
kappa
0.02777777777777777
kappa
0.016666666666666666
kappa
0.02777777777777777
kappa
0.04999999999999998
kappa
0.02222222222222221
kappa
0.011111111111111105
kappa
0.02222222222222221
kappa
0.07777777777777778
kappa
0.016666666666666666
kb_relative_information_score
0.09541977066501695
kb_relative_information_score
0.0849621957594095
kb_relative_information_score
0.07450462085380219
kb_relative_information_score
0.08496219575940904
kb_relative_information_score
0.1058773455706238
kb_relative_information_score
0.07973340830660601
kb_relative_information_score
0.06927583340099874
kb_relative_information_score
0.07973340830660595
kb_relative_information_score
0.1320212828346407
kb_relative_information_score
0.07450462085380236
mean_absolute_error
0.17299999999999977
mean_absolute_error
0.1749999999999998
mean_absolute_error
0.17699999999999982
mean_absolute_error
0.1749999999999998
mean_absolute_error
0.17099999999999974
mean_absolute_error
0.1759999999999998
mean_absolute_error
0.17799999999999983
mean_absolute_error
0.1759999999999998
mean_absolute_error
0.16599999999999965
mean_absolute_error
0.17699999999999982
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
0.1593867924528302 [1,0,0.375,0.2,0,0.018868,0,0,0,0]
precision
0.12212765957446808 [1,0,0,0.2,0,0,0,0,0.021277,0]
precision
0.12 [1,0,0.033333,0.166667,0,0,0,0,0,0]
precision
0.12420403126285479 [1,0,0.090909,0.058824,0.066667,0,0,0,0.025641,0]
precision
0.13308823529411765 [1,0,0.205882,0.125,0,0,0,0,0,0]
precision
0.11866666666666666 [1,0,0.12,0.066667,0,0,0,0,0,0]
precision
0.129 [1,0,0,0.25,0.04,0,0,0,0,0]
precision
0.13095238095238096 [1,0,0,0.142857,0,0.166667,0,0,0,0]
precision
0.17019822282980177 [1,0.030303,0.285714,0.333333,0,0,0,0,0,0.052632]
precision
0.14761904761904762 [1,0,0.142857,0.333333,0,0,0,0,0,0]
predictive_accuracy
0.135
predictive_accuracy
0.125
predictive_accuracy
0.115
predictive_accuracy
0.125
predictive_accuracy
0.145
predictive_accuracy
0.12
predictive_accuracy
0.11
predictive_accuracy
0.12
predictive_accuracy
0.17
predictive_accuracy
0.115
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
0.9611111111111108
relative_absolute_error
0.9722222222222221
relative_absolute_error
0.9833333333333334
relative_absolute_error
0.9722222222222221
relative_absolute_error
0.9499999999999996
relative_absolute_error
0.9777777777777777
relative_absolute_error
0.988888888888889
relative_absolute_error
0.9777777777777777
relative_absolute_error
0.9222222222222213
relative_absolute_error
0.9833333333333334
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
0.41593268686170815
root_mean_squared_error
0.4183300132670375
root_mean_squared_error
0.42071367935925236
root_mean_squared_error
0.4183300132670375
root_mean_squared_error
0.41352146256270633
root_mean_squared_error
0.41952353926806035
root_mean_squared_error
0.4219004621945795
root_mean_squared_error
0.41952353926806035
root_mean_squared_error
0.40743097574926684
root_mean_squared_error
0.42071367935925236
root_relative_squared_error
1.386442289539028
root_relative_squared_error
1.3944333775567928
root_relative_squared_error
1.4023789311975088
root_relative_squared_error
1.3944333775567928
root_relative_squared_error
1.378404875209022
root_relative_squared_error
1.3984117975602017
root_relative_squared_error
1.4063348739819324
root_relative_squared_error
1.3984117975602017
root_relative_squared_error
1.358103252497557
root_relative_squared_error
1.4023789311975088
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
0.13499999999999998 [0.95,0,0.15,0.2,0,0.05,0,0,0,0]
unweighted_recall
0.125 [1,0,0,0.2,0,0,0,0,0.05,0]
unweighted_recall
0.11499999999999999 [0.95,0,0.05,0.15,0,0,0,0,0,0]
unweighted_recall
0.12500000000000003 [1,0,0.05,0.05,0.1,0,0,0,0.05,0]
unweighted_recall
0.14500000000000002 [1,0,0.35,0.1,0,0,0,0,0,0]
unweighted_recall
0.12 [1,0,0.15,0.05,0,0,0,0,0,0]
unweighted_recall
0.11000000000000001 [0.95,0,0,0.1,0.05,0,0,0,0,0]
unweighted_recall
0.12 [1,0,0,0.15,0,0.05,0,0,0,0]
unweighted_recall
0.17 [1,0.05,0.1,0.5,0,0,0,0,0,0.05]
unweighted_recall
0.11500000000000002 [1,0,0.1,0.05,0,0,0,0,0,0]
usercpu_time_millis
46.875
usercpu_time_millis
46.875
usercpu_time_millis
46.875
usercpu_time_millis
62.5
usercpu_time_millis
46.875
usercpu_time_millis
46.875
usercpu_time_millis
46.875
usercpu_time_millis
46.875
usercpu_time_millis
46.875
usercpu_time_millis
31.25
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_testing
0
usercpu_time_millis_testing
0
usercpu_time_millis_testing
0
usercpu_time_millis_training
46.875
usercpu_time_millis_training
46.875
usercpu_time_millis_training
46.875
usercpu_time_millis_training
62.5
usercpu_time_millis_training
46.875
usercpu_time_millis_training
46.875
usercpu_time_millis_training
46.875
usercpu_time_millis_training
46.875
usercpu_time_millis_training
46.875
usercpu_time_millis_training
31.25
wall_clock_time_millis
42.97447204589844
wall_clock_time_millis
48.94852638244629
wall_clock_time_millis
55.96733093261719
wall_clock_time_millis
55.98807334899902
wall_clock_time_millis
48.97284507751465
wall_clock_time_millis
43.951988220214844
wall_clock_time_millis
43.9755916595459
wall_clock_time_millis
43.97463798522949
wall_clock_time_millis
45.95065116882324
wall_clock_time_millis
39.97635841369629
wall_clock_time_millis_testing
0
wall_clock_time_millis_testing
1.0004043579101562
wall_clock_time_millis_testing
0
wall_clock_time_millis_testing
0
wall_clock_time_millis_testing
1.0013580322265625
wall_clock_time_millis_testing
0.9999275207519531
wall_clock_time_millis_testing
1.0008811950683594
wall_clock_time_millis_testing
0.9999275207519531
wall_clock_time_millis_testing
0.9999275207519531
wall_clock_time_millis_testing
0.9999275207519531
wall_clock_time_millis_training
42.97447204589844
wall_clock_time_millis_training
47.94812202453613
wall_clock_time_millis_training
55.96733093261719
wall_clock_time_millis_training
55.98807334899902
wall_clock_time_millis_training
47.971487045288086
wall_clock_time_millis_training
42.95206069946289
wall_clock_time_millis_training
42.97471046447754
wall_clock_time_millis_training
42.97471046447754
wall_clock_time_millis_training
44.95072364807129
wall_clock_time_millis_training
38.976430892944336
weighted_recall
0.135 [0.95,0,0.15,0.2,0,0.05,0,0,0,0]
weighted_recall
0.125 [1,0,0,0.2,0,0,0,0,0.05,0]
weighted_recall
0.115 [0.95,0,0.05,0.15,0,0,0,0,0,0]
weighted_recall
0.125 [1,0,0.05,0.05,0.1,0,0,0,0.05,0]
weighted_recall
0.145 [1,0,0.35,0.1,0,0,0,0,0,0]
weighted_recall
0.12 [1,0,0.15,0.05,0,0,0,0,0,0]
weighted_recall
0.11 [0.95,0,0,0.1,0.05,0,0,0,0,0]
weighted_recall
0.12 [1,0,0,0.15,0,0.05,0,0,0,0]
weighted_recall
0.17 [1,0.05,0.1,0.5,0,0,0,0,0,0.05]
weighted_recall
0.115 [1,0,0.1,0.05,0,0,0,0,0,0]