10154630
7789
Sarim Zafar
18
Supervised Classification
8947
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,logisticregression=sklearn.linear_model.logistic.LogisticRegression)(1)
8080245
copy
true
8946
fill_value
null
8946
missing_values
NaN
8946
strategy
"mean"
8946
verbose
0
8946
memory
null
8947
C
1.0
8948
class_weight
null
8948
dual
false
8948
fit_intercept
true
8948
intercept_scaling
1
8948
max_iter
100
8948
multi_class
"warn"
8948
n_jobs
null
8948
penalty
"l2"
8948
random_state
13842
8948
solver
"warn"
8948
tol
0.0001
8948
verbose
0
8948
warm_start
false
8948
openml-python
Sklearn_0.20.2.
18
mfeat-morphological
https://www.openml.org/data/download/18/dataset_18_mfeat-morphological.arff
-1
21229827
description
https://www.openml.org/data/download/21229827/description.xml
-1
21229828
predictions
https://www.openml.org/data/download/21229828/predictions.arff
area_under_roc_curve
0.9504797222222221 [0.988853,0.988994,0.947136,0.891194,0.928972,0.955164,0.938235,0.954128,0.990617,0.921504]
average_cost
0
f_measure
0.6869735315303939 [0.992443,0.889435,0.697286,0.476454,0.534819,0.635097,0.608,0.719101,0.977099,0.34]
kappa
0.6644444444444444
kb_relative_information_score
1166.1499716015294
mean_absolute_error
0.11594978595957081
mean_prior_absolute_error
0.18000000000000554
number_of_instances
2000 [200,200,200,200,200,200,200,200,200,200]
precision
0.6992425195179994 [1,0.874396,0.598566,0.534161,0.603774,0.716981,0.506667,0.653061,0.994819,0.51]
predictive_accuracy
0.698
prior_entropy
3.321928094887362
recall
0.698 [0.985,0.905,0.835,0.43,0.48,0.57,0.76,0.8,0.96,0.255]
relative_absolute_error
0.6441654775531512
root_mean_prior_squared_error
0.3000000000000046
root_mean_squared_error
0.21905922658208052
root_relative_squared_error
0.7301974219402573
total_cost
0
area_under_roc_curve
0.9269722222222224 [0.951667,0.968611,0.915,0.8425,0.919722,0.939722,0.936389,0.954444,1,0.841667]
area_under_roc_curve
0.9565555555555556 [1,0.994722,0.945556,0.922222,0.9025,0.958056,0.945694,0.964167,0.989722,0.942917]
area_under_roc_curve
0.9488333333333334 [0.957778,0.997778,0.975,0.913056,0.940833,0.921944,0.892361,0.950833,1,0.93875]
area_under_roc_curve
0.9537777777777776 [1,0.998889,0.934444,0.86,0.938333,0.976111,0.95875,0.958611,0.988611,0.924028]
area_under_roc_curve
0.9514444444444444 [1,0.999444,0.957778,0.843056,0.946389,0.946944,0.951667,0.946667,0.988889,0.933611]
area_under_roc_curve
0.9589166666666665 [1,0.978611,0.93,0.94,0.934722,0.965833,0.954583,0.951111,1,0.934306]
area_under_roc_curve
0.9555555555555557 [0.976667,0.994722,0.954167,0.923333,0.957222,0.947222,0.937917,0.950556,1,0.91375]
area_under_roc_curve
0.9592222222222223 [1,0.994444,0.976111,0.891111,0.938889,0.970278,0.942361,0.968611,0.965,0.945417]
area_under_roc_curve
0.9415555555555555 [1,0.968611,0.921944,0.882778,0.876667,0.954167,0.931389,0.971111,0.9875,0.921389]
area_under_roc_curve
0.961638888888889 [1,0.998333,0.964444,0.901667,0.946667,0.975833,0.947361,0.9575,0.983056,0.941528]
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
0.6994458438307075 [0.974359,0.780488,0.636364,0.4375,0.594595,0.6,0.647059,0.666667,0.97561,0.681818]
f_measure
0.6268289333405612 [1,0.837209,0.581818,0.5,0.424242,0.484848,0.576923,0.666667,0.974359,0.222222]
f_measure
0.6526709071834371 [0.974359,0.952381,0.716981,0.333333,0.5,0.529412,0.576923,0.789474,1,0.153846]
f_measure
0.7081255103006677 [1,0.930233,0.680851,0.5,0.516129,0.789474,0.653846,0.636364,0.974359,0.4]
f_measure
0.6866926725792807 [1,0.926829,0.727273,0.428571,0.580645,0.588235,0.511628,0.708333,0.974359,0.421053]
f_measure
0.6921007518272595 [1,0.9,0.727273,0.564103,0.451613,0.65,0.5,0.73913,1,0.388889]
f_measure
0.6947201142315461 [0.974359,0.9,0.723404,0.555556,0.634146,0.588235,0.678571,0.711111,1,0.181818]
f_measure
0.6980825114193978 [1,0.923077,0.77551,0.470588,0.514286,0.666667,0.641509,0.765957,0.947368,0.275862]
f_measure
0.6833692283344931 [1,0.878049,0.705882,0.486486,0.540541,0.647059,0.592593,0.75,0.947368,0.285714]
kappa
0.6722222222222222
kappa
0.6055555555555556
kappa
0.638888888888889
kappa
0.6888888888888889
kappa
0.6555555555555556
kappa
0.6666666666666666
kappa
0.6888888888888889
kappa
0.6833333333333333
kappa
0.6833333333333333
kappa
0.6611111111111111
kb_relative_information_score
112.49069312175598
kb_relative_information_score
114.77150588984216
kb_relative_information_score
115.06689209029159
kb_relative_information_score
116.89842518734444
kb_relative_information_score
116.30549272767152
kb_relative_information_score
117.90343684463478
kb_relative_information_score
119.43192602541447
kb_relative_information_score
119.62892715180077
kb_relative_information_score
115.85178041605397
kb_relative_information_score
117.80089214671692
mean_absolute_error
0.11772598016344854
mean_absolute_error
0.11821659301475906
mean_absolute_error
0.11767303749397583
mean_absolute_error
0.11567087879540662
mean_absolute_error
0.11577235294685902
mean_absolute_error
0.11575172520865212
mean_absolute_error
0.11395678537215707
mean_absolute_error
0.11381734995004208
mean_absolute_error
0.1155216616623739
mean_absolute_error
0.11539149498803346
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
0.711015406162465 [1,0.761905,0.583333,0.583333,0.647059,0.6,0.785714,0.571429,0.952381,0.625]
precision
0.648978277157625 [1,0.782609,0.457143,0.5625,0.538462,0.615385,0.46875,0.636364,1,0.428571]
precision
0.6638122294372295 [1,0.909091,0.575758,0.375,0.5,0.642857,0.46875,0.833333,1,0.333333]
precision
0.7299847203923292 [1,0.869565,0.592593,0.5625,0.727273,0.833333,0.53125,0.583333,1,0.6]
precision
0.7042835184139533 [1,0.904762,0.666667,0.409091,0.818182,0.714286,0.478261,0.607143,1,0.444444]
precision
0.6981657158630843 [1,0.9,0.666667,0.578947,0.636364,0.65,0.458333,0.653846,1,0.4375]
precision
0.7655740740740741 [1,0.9,0.62963,0.625,0.619048,0.714286,0.527778,0.64,1,1]
precision
0.7150232032536933 [1,0.947368,0.655172,0.571429,0.6,0.75,0.515152,0.666667,1,0.444444]
precision
0.7061737598265111 [1,0.857143,0.580645,0.529412,0.588235,0.785714,0.470588,0.75,1,0.5]
predictive_accuracy
0.705
predictive_accuracy
0.645
predictive_accuracy
0.675
predictive_accuracy
0.72
predictive_accuracy
0.69
predictive_accuracy
0.7
predictive_accuracy
0.72
predictive_accuracy
0.715
predictive_accuracy
0.715
predictive_accuracy
0.695
prior_entropy
3.321928094887362
prior_entropy
3.321928094887362
prior_entropy
3.321928094887362
prior_entropy
3.321928094887362
prior_entropy
3.321928094887362
prior_entropy
3.321928094887362
prior_entropy
3.321928094887362
prior_entropy
3.321928094887362
prior_entropy
3.321928094887362
prior_entropy
3.321928094887362
recall
0.705 [0.95,0.8,0.7,0.35,0.55,0.6,0.55,0.8,1,0.75]
recall
0.645 [1,0.9,0.8,0.45,0.35,0.4,0.75,0.7,0.95,0.15]
recall
0.675 [0.95,1,0.95,0.3,0.5,0.45,0.75,0.75,1,0.1]
recall
0.72 [1,1,0.8,0.45,0.4,0.75,0.85,0.7,0.95,0.3]
recall
0.69 [1,0.95,0.8,0.45,0.45,0.5,0.55,0.85,0.95,0.4]
recall
0.7 [1,0.9,0.8,0.55,0.35,0.65,0.55,0.85,1,0.35]
recall
0.72 [0.95,0.9,0.85,0.5,0.65,0.5,0.95,0.8,1,0.1]
recall
0.715 [1,0.9,0.95,0.4,0.45,0.6,0.85,0.9,0.9,0.2]
recall
0.715 [1,0.8,0.8,0.4,0.6,0.7,1,0.9,0.95,0]
recall
0.695 [1,0.9,0.9,0.45,0.5,0.55,0.8,0.75,0.9,0.2]
relative_absolute_error
0.6540332231302705
relative_absolute_error
0.6567588500819955
relative_absolute_error
0.6537390971887552
relative_absolute_error
0.6426159933078153
relative_absolute_error
0.643179738593662
relative_absolute_error
0.6430651400480681
relative_absolute_error
0.63309325206754
relative_absolute_error
0.6323186108335679
relative_absolute_error
0.6417870092354113
relative_absolute_error
0.641063861044631
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
0.22554327958395867
root_mean_squared_error
0.22126019185562582
root_mean_squared_error
0.22122062735076428
root_mean_squared_error
0.21753578604802706
root_mean_squared_error
0.2194477966589703
root_mean_squared_error
0.21717652378713098
root_mean_squared_error
0.21627908990809838
root_mean_squared_error
0.21546590163508372
root_mean_squared_error
0.21956245814778838
root_mean_squared_error
0.21691097112729157
root_relative_squared_error
0.7518109319465293
root_relative_squared_error
0.7375339728520864
root_relative_squared_error
0.7374020911692147
root_relative_squared_error
0.7251192868267573
root_relative_squared_error
0.7314926555299014
root_relative_squared_error
0.7239217459571037
root_relative_squared_error
0.7209302996936617
root_relative_squared_error
0.7182196721169462
root_relative_squared_error
0.7318748604926284
root_relative_squared_error
0.7230365704243057
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