10588186
32117
VAIBHAV JAISWAL
18
Supervised Classification
19161
sklearn.pipeline.Pipeline(numerical=sklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,scaler=sklearn.preprocessing._data.StandardScaler),model=sklearn.neighbors._classification.KNeighborsClassifier)(1)
8304079
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
algorithm
"auto"
19154
leaf_size
30
19154
metric
"minkowski"
19154
metric_params
null
19154
n_jobs
null
19154
n_neighbors
5
19154
p
2
19154
weights
"uniform"
19154
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
19161
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"}}]
19161
verbose
false
19161
openml-python
Sklearn_1.0.2.
18
mfeat-morphological
https://www.openml.org/data/download/18/dataset_18_mfeat-morphological.arff
-1
22103939
description
https://api.openml.org/data/download/22103939/description.xml
-1
22103940
predictions
https://api.openml.org/data/download/22103940/predictions.arff
area_under_roc_curve
0.5073059722222223 [0.992475,0.407893,0.535013,0.613896,0.447218,0.386739,0.409167,0.443333,0.402165,0.435161]
average_cost
0
f_measure
0.1311280214447002 [0.992443,0.004706,0.105528,0.193069,0.005277,0,0,0,0.005168,0.005089]
kappa
0.033888888888888885
kb_relative_information_score
0.10938677533784937
mean_absolute_error
0.17315999999999504
mean_prior_absolute_error
0.18000000000000554
weighted_recall
0.1305 [0.985,0.005,0.105,0.195,0.005,0,0,0,0.005,0.005]
number_of_instances
2000 [200,200,200,200,200,200,200,200,200,200]
precision
0.13177970540052036 [1,0.004444,0.106061,0.191176,0.005587,0,0,0,0.005348,0.005181]
predictive_accuracy
0.1305
prior_entropy
3.3219280948872383
relative_absolute_error
0.9619999999999429
root_mean_prior_squared_error
0.3000000000000046
root_mean_squared_error
0.38351531912036807
root_relative_squared_error
1.2783843970678739
total_cost
0
unweighted_recall
0.13049999999999998 [0.985,0.005,0.105,0.195,0.005,0,0,0,0.005,0.005]
area_under_roc_curve
0.5052222222222222 [0.974722,0.4,0.523056,0.683472,0.409861,0.391667,0.402778,0.444444,0.394444,0.427778]
area_under_roc_curve
0.5039305555555554 [1,0.399444,0.568194,0.592778,0.416667,0.380556,0.4,0.441667,0.412222,0.427778]
area_under_roc_curve
0.49919444444444444 [0.975,0.380556,0.504444,0.632083,0.433194,0.394444,0.425,0.444444,0.383333,0.419444]
area_under_roc_curve
0.49888888888888877 [1,0.408333,0.507917,0.54875,0.439722,0.377778,0.416667,0.438889,0.400833,0.45]
area_under_roc_curve
0.5173194444444443 [1,0.402778,0.578333,0.655139,0.450556,0.400833,0.408333,0.444444,0.402222,0.430556]
area_under_roc_curve
0.5174027777777777 [1,0.402778,0.612083,0.510139,0.568472,0.386111,0.416667,0.444444,0.391667,0.441667]
area_under_roc_curve
0.5011527777777777 [0.974861,0.415417,0.503333,0.591528,0.454167,0.391667,0.413889,0.441667,0.391667,0.433333]
area_under_roc_curve
0.507625 [1,0.420278,0.5225,0.639028,0.40875,0.377778,0.405556,0.444444,0.421806,0.436111]
area_under_roc_curve
0.5187916666666667 [1,0.443333,0.520417,0.676944,0.477639,0.383333,0.397222,0.444444,0.400278,0.444306]
area_under_roc_curve
0.5031111111111111 [1,0.405556,0.51,0.604028,0.412917,0.383333,0.405556,0.444444,0.423611,0.441667]
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
0.13663003663003662 [0.974359,0,0.153846,0.238095,0,0,0,0,0,0]
f_measure
0.14357142857142857 [1,0,0.15,0.285714,0,0,0,0,0,0]
f_measure
0.1177708256655625 [0.974359,0,0.045455,0.157895,0,0,0,0,0,0]
f_measure
0.12549923195084486 [1,0,0.064516,0.190476,0,0,0,0,0,0]
f_measure
0.129020979020979 [1,0,0.136364,0.153846,0,0,0,0,0,0]
f_measure
0.1289232886136911 [1,0,0.177778,0.058824,0.052632,0,0,0,0,0]
f_measure
0.11694809255784865 [0.974359,0,0,0.195122,0,0,0,0,0,0]
f_measure
0.12577597840755736 [1,0,0.052632,0.205128,0,0,0,0,0,0]
f_measure
0.1452136704433406 [1,0.04878,0.133333,0.217391,0,0,0,0,0,0.052632]
f_measure
0.13497416872345971 [1,0,0.108108,0.195122,0,0,0,0,0.046512,0]
kappa
0.03888888888888889
kappa
0.04999999999999998
kappa
0.016666666666666666
kappa
0.02777777777777777
kappa
0.03333333333333333
kappa
0.03333333333333333
kappa
0.016666666666666666
kappa
0.02777777777777777
kappa
0.05555555555555554
kappa
0.03888888888888889
kb_relative_information_score
0.1092541260624001
kb_relative_information_score
0.11362943237935864
kb_relative_information_score
0.09362943237935832
kb_relative_information_score
0.10039034496991536
kb_relative_information_score
0.1187772943538614
kb_relative_information_score
0.11315260067081992
kb_relative_information_score
0.09476565128687374
kb_relative_information_score
0.11445593835576996
kb_relative_information_score
0.12852153174162453
kb_relative_information_score
0.10729140117847344
mean_absolute_error
0.17339999999999983
mean_absolute_error
0.1721999999999998
mean_absolute_error
0.17559999999999984
mean_absolute_error
0.1741999999999998
mean_absolute_error
0.1717999999999998
mean_absolute_error
0.17299999999999982
mean_absolute_error
0.17539999999999986
mean_absolute_error
0.1727999999999998
mean_absolute_error
0.1701999999999998
mean_absolute_error
0.1729999999999998
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
0.13851674641148326 [1,0,0.157895,0.227273,0,0,0,0,0,0]
precision
0.14227272727272727 [1,0,0.15,0.272727,0,0,0,0,0,0]
precision
0.12083333333333332 [1,0,0.041667,0.166667,0,0,0,0,0,0]
precision
0.1272727272727273 [1,0,0.090909,0.181818,0,0,0,0,0,0]
precision
0.12828947368421054 [1,0,0.125,0.157895,0,0,0,0,0,0]
precision
0.12869841269841267 [1,0,0.16,0.071429,0.055556,0,0,0,0,0]
precision
0.11904761904761905 [1,0,0,0.190476,0,0,0,0,0,0]
precision
0.12660818713450292 [1,0,0.055556,0.210526,0,0,0,0,0,0]
precision
0.14154822954822954 [1,0.047619,0.12,0.192308,0,0,0,0,0,0.055556]
precision
0.13516015101692852 [1,0,0.117647,0.190476,0,0,0,0,0.043478,0]
predictive_accuracy
0.135
predictive_accuracy
0.145
predictive_accuracy
0.115
predictive_accuracy
0.125
predictive_accuracy
0.13
predictive_accuracy
0.13
predictive_accuracy
0.115
predictive_accuracy
0.125
predictive_accuracy
0.15
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
0.9633333333333334
relative_absolute_error
0.9566666666666667
relative_absolute_error
0.9755555555555557
relative_absolute_error
0.9677777777777777
relative_absolute_error
0.9544444444444443
relative_absolute_error
0.9611111111111112
relative_absolute_error
0.9744444444444447
relative_absolute_error
0.96
relative_absolute_error
0.9455555555555555
relative_absolute_error
0.961111111111111
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
0.3829360259886759
root_mean_squared_error
0.38136596596969663
root_mean_squared_error
0.3879175170058705
root_mean_squared_error
0.38538292645108174
root_mean_squared_error
0.3830926780819489
root_mean_squared_error
0.3823087757297757
root_mean_squared_error
0.3896151947755629
root_mean_squared_error
0.3787875393937872
root_mean_squared_error
0.3768288736283352
root_mean_squared_error
0.38672987989034396
root_relative_squared_error
1.2764534199622537
root_relative_squared_error
1.271219886565656
root_relative_squared_error
1.2930583900195691
root_relative_squared_error
1.2846097548369397
root_relative_squared_error
1.276975593606497
root_relative_squared_error
1.2743625857659198
root_relative_squared_error
1.2987173159185437
root_relative_squared_error
1.2626251313126247
root_relative_squared_error
1.2560962454277849
root_relative_squared_error
1.2890995996344807
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 [0.95,0,0.15,0.25,0,0,0,0,0,0]
unweighted_recall
0.145 [1,0,0.15,0.3,0,0,0,0,0,0]
unweighted_recall
0.11499999999999999 [0.95,0,0.05,0.15,0,0,0,0,0,0]
unweighted_recall
0.125 [1,0,0.05,0.2,0,0,0,0,0,0]
unweighted_recall
0.12999999999999998 [1,0,0.15,0.15,0,0,0,0,0,0]
unweighted_recall
0.13 [1,0,0.2,0.05,0.05,0,0,0,0,0]
unweighted_recall
0.11499999999999999 [0.95,0,0,0.2,0,0,0,0,0,0]
unweighted_recall
0.125 [1,0,0.05,0.2,0,0,0,0,0,0]
unweighted_recall
0.15 [1,0.05,0.15,0.25,0,0,0,0,0,0.05]
unweighted_recall
0.135 [1,0,0.1,0.2,0,0,0,0,0.05,0]
usercpu_time_millis
31.25
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
15.625
usercpu_time_millis
15.625
usercpu_time_millis
15.625
usercpu_time_millis
15.625
usercpu_time_millis_testing
15.625
usercpu_time_millis_testing
15.625
usercpu_time_millis_testing
15.625
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
15.625
usercpu_time_millis_testing
15.625
usercpu_time_millis_testing
15.625
usercpu_time_millis_training
15.625
usercpu_time_millis_training
0
usercpu_time_millis_training
0
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
0
wall_clock_time_millis
23.980140686035156
wall_clock_time_millis
12.99142837524414
wall_clock_time_millis
13.990640640258789
wall_clock_time_millis
14.970541000366211
wall_clock_time_millis
14.970779418945312
wall_clock_time_millis
14.989852905273438
wall_clock_time_millis
13.971090316772461
wall_clock_time_millis
14.989614486694336
wall_clock_time_millis
14.990568161010742
wall_clock_time_millis
14.989614486694336
wall_clock_time_millis_testing
14.99176025390625
wall_clock_time_millis_testing
7.99560546875
wall_clock_time_millis_testing
8.994817733764648
wall_clock_time_millis_testing
9.973764419555664
wall_clock_time_millis_testing
9.974241256713867
wall_clock_time_millis_testing
9.994029998779297
wall_clock_time_millis_testing
8.97526741027832
wall_clock_time_millis_testing
9.994983673095703
wall_clock_time_millis_testing
9.994983673095703
wall_clock_time_millis_testing
9.994745254516602
wall_clock_time_millis_training
8.988380432128906
wall_clock_time_millis_training
4.995822906494141
wall_clock_time_millis_training
4.995822906494141
wall_clock_time_millis_training
4.996776580810547
wall_clock_time_millis_training
4.996538162231445
wall_clock_time_millis_training
4.995822906494141
wall_clock_time_millis_training
4.995822906494141
wall_clock_time_millis_training
4.994630813598633
wall_clock_time_millis_training
4.995584487915039
wall_clock_time_millis_training
4.994869232177734
weighted_recall
0.135 [0.95,0,0.15,0.25,0,0,0,0,0,0]
weighted_recall
0.145 [1,0,0.15,0.3,0,0,0,0,0,0]
weighted_recall
0.115 [0.95,0,0.05,0.15,0,0,0,0,0,0]
weighted_recall
0.125 [1,0,0.05,0.2,0,0,0,0,0,0]
weighted_recall
0.13 [1,0,0.15,0.15,0,0,0,0,0,0]
weighted_recall
0.13 [1,0,0.2,0.05,0.05,0,0,0,0,0]
weighted_recall
0.115 [0.95,0,0,0.2,0,0,0,0,0,0]
weighted_recall
0.125 [1,0,0.05,0.2,0,0,0,0,0,0]
weighted_recall
0.15 [1,0.05,0.15,0.25,0,0,0,0,0,0.05]
weighted_recall
0.135 [1,0,0.1,0.2,0,0,0,0,0.05,0]