10588254
32117
VAIBHAV JAISWAL
18
Supervised Classification
19176
sklearn.pipeline.Pipeline(numerical=sklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,scaler=sklearn.preprocessing._data.StandardScaler),model=sklearn.neural_network._multilayer_perceptron.MLPClassifier)(1)
8304110
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
19176
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"}}]
19176
verbose
false
19176
activation
"relu"
19177
alpha
0.0001
19177
batch_size
"auto"
19177
beta_1
0.9
19177
beta_2
0.999
19177
early_stopping
false
19177
epsilon
1e-08
19177
hidden_layer_sizes
[100]
19177
learning_rate
"constant"
19177
learning_rate_init
0.001
19177
max_fun
15000
19177
max_iter
5000
19177
momentum
0.9
19177
n_iter_no_change
10
19177
nesterovs_momentum
true
19177
power_t
0.5
19177
random_state
0
19177
shuffle
true
19177
solver
"adam"
19177
tol
0.0001
19177
validation_fraction
0.1
19177
verbose
false
19177
warm_start
false
19177
openml-python
Sklearn_1.0.2.
18
mfeat-morphological
https://www.openml.org/data/download/18/dataset_18_mfeat-morphological.arff
-1
22104075
description
https://api.openml.org/data/download/22104075/description.xml
-1
22104076
predictions
https://api.openml.org/data/download/22104076/predictions.arff
area_under_roc_curve
0.509278888888889 [0.999797,0.375039,0.691672,0.764033,0.659447,0.309967,0.391864,0.208228,0.154597,0.538144]
average_cost
0
f_measure
0.12528424181521852 [0.992443,0,0.069519,0.169492,0,0,0,0,0.016438,0.00495]
kappa
0.027222222222222214
kb_relative_information_score
0.09925930739398094
mean_absolute_error
0.1735932661494544
mean_prior_absolute_error
0.18000000000000554
weighted_recall
0.1245 [0.985,0,0.065,0.175,0,0,0,0,0.015,0.005]
number_of_instances
2000 [200,200,200,200,200,200,200,200,200,200]
precision
0.12621156714705836 [1,0,0.074713,0.164319,0,0,0,0,0.018182,0.004902]
predictive_accuracy
0.1245
prior_entropy
3.3219280948872383
relative_absolute_error
0.9644070341636057
root_mean_prior_squared_error
0.3000000000000046
root_mean_squared_error
0.3793466779582967
root_relative_squared_error
1.2644889265276362
total_cost
0
unweighted_recall
0.12449999999999999 [0.985,0,0.065,0.175,0,0,0,0,0.015,0.005]
area_under_roc_curve
0.5410555555555555 [1,0.342222,0.685,0.796111,0.636667,0.331111,0.482083,0.252222,0.350556,0.534583]
area_under_roc_curve
0.5034722222222222 [1,0.39,0.744167,0.765833,0.678611,0.23,0.380556,0.220278,0.094167,0.531111]
area_under_roc_curve
0.5068888888888889 [0.999444,0.3425,0.653056,0.779444,0.672778,0.488889,0.347917,0.200556,0.086667,0.497639]
area_under_roc_curve
0.4953888888888888 [1,0.398056,0.655278,0.708333,0.661944,0.247778,0.364167,0.212222,0.153611,0.5525]
area_under_roc_curve
0.5164166666666666 [1,0.409444,0.695,0.8,0.702222,0.326111,0.379722,0.169722,0.161389,0.520556]
area_under_roc_curve
0.4975555555555555 [1,0.405833,0.696111,0.689167,0.671111,0.289722,0.431667,0.145278,0.065,0.581667]
area_under_roc_curve
0.4772777777777778 [0.999167,0.334167,0.693889,0.778056,0.656944,0.080556,0.399306,0.213056,0.0575,0.560139]
area_under_roc_curve
0.5167222222222223 [1,0.375,0.682222,0.789722,0.628889,0.321667,0.37,0.215556,0.248056,0.536111]
area_under_roc_curve
0.5201944444444444 [1,0.361667,0.696944,0.767222,0.644167,0.375833,0.3675,0.241944,0.196667,0.55]
area_under_roc_curve
0.5023611111111111 [1,0.385833,0.700556,0.750278,0.639722,0.263611,0.394583,0.211667,0.163611,0.51375]
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
0.12886446886446884 [0.974359,0,0.114286,0.2,0,0,0,0,0,0]
f_measure
0.11969111969111969 [1,0,0.054054,0.142857,0,0,0,0,0,0]
f_measure
0.1171978021978022 [0.974359,0,0.047619,0.15,0,0,0,0,0,0]
f_measure
0.12151315789473685 [1,0,0.0625,0.1,0,0,0,0,0.052632,0]
f_measure
0.13779904306220095 [1,0,0.105263,0.272727,0,0,0,0,0,0]
f_measure
0.11449631449631449 [1,0,0.090909,0.054054,0,0,0,0,0,0]
f_measure
0.11694809255784865 [0.974359,0,0,0.195122,0,0,0,0,0,0]
f_measure
0.11941391941391942 [1,0,0,0.142857,0,0,0,0,0.051282,0]
f_measure
0.1375159119839971 [1,0,0.111111,0.212766,0,0,0,0,0,0.051282]
f_measure
0.1360797342192691 [1,0,0.114286,0.2,0,0,0,0,0.046512,0]
kappa
0.02777777777777777
kappa
0.02222222222222221
kappa
0.016666666666666666
kappa
0.02222222222222221
kappa
0.04444444444444445
kappa
0.016666666666666666
kappa
0.016666666666666666
kappa
0.02222222222222221
kappa
0.04444444444444445
kappa
0.03888888888888889
kb_relative_information_score
0.10712045254106675
kb_relative_information_score
0.10602854842014578
kb_relative_information_score
0.0882299696044493
kb_relative_information_score
0.09249827536613915
kb_relative_information_score
0.11080064845915048
kb_relative_information_score
0.0879129614729517
kb_relative_information_score
0.08332969874936685
kb_relative_information_score
0.09639733710284419
kb_relative_information_score
0.11898257605772279
kb_relative_information_score
0.10129260616593969
mean_absolute_error
0.17328097521045416
mean_absolute_error
0.17277615854664327
mean_absolute_error
0.17551123684677275
mean_absolute_error
0.17435074178365387
mean_absolute_error
0.17188493265127835
mean_absolute_error
0.1753670482738938
mean_absolute_error
0.17555414988280943
mean_absolute_error
0.17430722754649955
mean_absolute_error
0.17000739359349837
mean_absolute_error
0.17289279715904218
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
0.13333333333333333 [1,0,0.133333,0.2,0,0,0,0,0,0]
precision
0.1195187165775401 [1,0,0.058824,0.136364,0,0,0,0,0,0]
precision
0.11954545454545455 [1,0,0.045455,0.15,0,0,0,0,0,0]
precision
0.1238888888888889 [1,0,0.083333,0.1,0,0,0,0,0.055556,0]
precision
0.1361111111111111 [1,0,0.111111,0.25,0,0,0,0,0,0]
precision
0.1142156862745098 [1,0,0.083333,0.058824,0,0,0,0,0,0]
precision
0.11904761904761905 [1,0,0,0.190476,0,0,0,0,0,0]
precision
0.11889952153110048 [1,0,0,0.136364,0,0,0,0,0.052632,0]
precision
0.13628167641325536 [1,0,0.125,0.185185,0,0,0,0,0,0.052632]
precision
0.13768115942028986 [1,0,0.133333,0.2,0,0,0,0,0.043478,0]
predictive_accuracy
0.125
predictive_accuracy
0.12
predictive_accuracy
0.115
predictive_accuracy
0.12
predictive_accuracy
0.14
predictive_accuracy
0.115
predictive_accuracy
0.115
predictive_accuracy
0.12
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
0.9626720845025241
relative_absolute_error
0.9598675474813525
relative_absolute_error
0.9750624269265163
relative_absolute_error
0.9686152321314114
relative_absolute_error
0.9549162925071031
relative_absolute_error
0.974261379299411
relative_absolute_error
0.9753008326822757
relative_absolute_error
0.9683734863694431
relative_absolute_error
0.9444855199638809
relative_absolute_error
0.9605155397724576
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
0.3780870156408469
root_mean_squared_error
0.37648636243472344
root_mean_squared_error
0.38111603669143884
root_mean_squared_error
0.3814451626384764
root_mean_squared_error
0.3777447471340074
root_mean_squared_error
0.38240845942729795
root_mean_squared_error
0.38469277356898096
root_mean_squared_error
0.37843986300172455
root_mean_squared_error
0.37373140261315946
root_mean_squared_error
0.37919606760577684
root_relative_squared_error
1.260290052136157
root_relative_squared_error
1.254954541449079
root_relative_squared_error
1.2703867889714635
root_relative_squared_error
1.271483875461589
root_relative_squared_error
1.2591491571133588
root_relative_squared_error
1.2746948647576608
root_relative_squared_error
1.2823092452299374
root_relative_squared_error
1.2614662100057492
root_relative_squared_error
1.2457713420438656
root_relative_squared_error
1.263986892019257
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
0.125 [0.95,0,0.1,0.2,0,0,0,0,0,0]
unweighted_recall
0.12 [1,0,0.05,0.15,0,0,0,0,0,0]
unweighted_recall
0.11499999999999999 [0.95,0,0.05,0.15,0,0,0,0,0,0]
unweighted_recall
0.12000000000000002 [1,0,0.05,0.1,0,0,0,0,0.05,0]
unweighted_recall
0.14 [1,0,0.1,0.3,0,0,0,0,0,0]
unweighted_recall
0.11500000000000002 [1,0,0.1,0.05,0,0,0,0,0,0]
unweighted_recall
0.11499999999999999 [0.95,0,0,0.2,0,0,0,0,0,0]
unweighted_recall
0.12 [1,0,0,0.15,0,0,0,0,0.05,0]
unweighted_recall
0.14 [1,0,0.1,0.25,0,0,0,0,0,0.05]
unweighted_recall
0.135 [1,0,0.1,0.2,0,0,0,0,0.05,0]
usercpu_time_millis
4875
usercpu_time_millis
4265.625
usercpu_time_millis
5437.5
usercpu_time_millis
5250
usercpu_time_millis
5171.875
usercpu_time_millis
5062.5
usercpu_time_millis
5078.125
usercpu_time_millis
5875
usercpu_time_millis
5078.125
usercpu_time_millis
5578.125
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
4875
usercpu_time_millis_training
4265.625
usercpu_time_millis_training
5437.5
usercpu_time_millis_training
5250
usercpu_time_millis_training
5171.875
usercpu_time_millis_training
5062.5
usercpu_time_millis_training
5078.125
usercpu_time_millis_training
5875
usercpu_time_millis_training
5078.125
usercpu_time_millis_training
5578.125
wall_clock_time_millis
4903.190135955811
wall_clock_time_millis
4295.536518096924
wall_clock_time_millis
5454.87380027771
wall_clock_time_millis
5251.988410949707
wall_clock_time_millis
5172.036170959473
wall_clock_time_millis
5058.100461959839
wall_clock_time_millis
5081.106424331665
wall_clock_time_millis
5863.6579513549805
wall_clock_time_millis
5087.063312530518
wall_clock_time_millis
5589.816093444824
wall_clock_time_millis_testing
0.9982585906982422
wall_clock_time_millis_testing
1.0004043579101562
wall_clock_time_millis_testing
0.9987354278564453
wall_clock_time_millis_testing
1.0006427764892578
wall_clock_time_millis_testing
0.99945068359375
wall_clock_time_millis_testing
0
wall_clock_time_millis_testing
0.99945068359375
wall_clock_time_millis_testing
0.9992122650146484
wall_clock_time_millis_testing
0
wall_clock_time_millis_testing
1.0001659393310547
wall_clock_time_millis_training
4902.191877365112
wall_clock_time_millis_training
4294.536113739014
wall_clock_time_millis_training
5453.8750648498535
wall_clock_time_millis_training
5250.987768173218
wall_clock_time_millis_training
5171.036720275879
wall_clock_time_millis_training
5058.100461959839
wall_clock_time_millis_training
5080.106973648071
wall_clock_time_millis_training
5862.658739089966
wall_clock_time_millis_training
5087.063312530518
wall_clock_time_millis_training
5588.815927505493
weighted_recall
0.125 [0.95,0,0.1,0.2,0,0,0,0,0,0]
weighted_recall
0.12 [1,0,0.05,0.15,0,0,0,0,0,0]
weighted_recall
0.115 [0.95,0,0.05,0.15,0,0,0,0,0,0]
weighted_recall
0.12 [1,0,0.05,0.1,0,0,0,0,0.05,0]
weighted_recall
0.14 [1,0,0.1,0.3,0,0,0,0,0,0]
weighted_recall
0.115 [1,0,0.1,0.05,0,0,0,0,0,0]
weighted_recall
0.115 [0.95,0,0,0.2,0,0,0,0,0,0]
weighted_recall
0.12 [1,0,0,0.15,0,0,0,0,0.05,0]
weighted_recall
0.14 [1,0,0.1,0.25,0,0,0,0,0,0.05]
weighted_recall
0.135 [1,0,0.1,0.2,0,0,0,0,0.05,0]