10147459
1
Jan van Rijn
14
Supervised Classification
8815
sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),variancethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,decisiontreeclassifier=sklearn.tree.tree.DecisionTreeClassifier)(1)
8073082
axis
0
8778
copy
true
8778
missing_values
"NaN"
8778
strategy
"most_frequent"
8778
verbose
0
8778
copy
true
8779
with_mean
true
8779
with_std
true
8779
memory
null
8780
copy
true
8781
fill_value
-1
8781
missing_values
NaN
8781
strategy
"constant"
8781
verbose
0
8781
categorical_features
null
8782
categories
null
8782
dtype
{"oml-python:serialized_object": "type", "value": "np.float64"}
8782
handle_unknown
"ignore"
8782
n_values
null
8782
sparse
true
8782
class_weight
null
8783
criterion
"gini"
8783
max_depth
null
8783
max_features
1.0
8783
max_leaf_nodes
null
8783
min_impurity_decrease
0.0
8783
min_impurity_split
null
8783
min_samples_leaf
4
8783
min_samples_split
11
8783
min_weight_fraction_leaf
0.0
8783
presort
false
8783
random_state
14419
8783
splitter
"best"
8783
n_jobs
null
8812
remainder
"passthrough"
8812
sparse_threshold
0.3
8812
transformer_weights
null
8812
memory
null
8813
memory
null
8815
threshold
0.0
8816
openml-python
Sklearn_0.20.0.
14
mfeat-fourier
https://www.openml.org/data/download/14/dataset_14_mfeat-fourier.arff
-1
21215457
description
https://api.openml.org/data/download/21215457/description.xml
-1
21215458
predictions
https://api.openml.org/data/download/21215458/predictions.arff
area_under_roc_curve
0.9011068055555554 [0.993839,0.850758,0.94605,0.918335,0.863726,0.920879,0.795729,0.953301,0.980367,0.788083]
average_cost
0
f_measure
0.751322955612765 [0.975369,0.678663,0.863636,0.807882,0.665012,0.827411,0.508159,0.797101,0.94026,0.449735]
kappa
0.7233333333333334
kb_relative_information_score
1508.9574893578067
mean_absolute_error
0.053226507936508245
mean_prior_absolute_error
0.18000000000000554
number_of_instances
2000 [200,200,200,200,200,200,200,200,200,200]
precision
0.7531364977537379 [0.961165,0.698413,0.872449,0.796117,0.660099,0.840206,0.475983,0.771028,0.978378,0.477528]
predictive_accuracy
0.7509999999999999
prior_entropy
3.321928094887362
recall
0.751 [0.99,0.66,0.855,0.82,0.67,0.815,0.545,0.825,0.905,0.425]
relative_absolute_error
0.2957028218694811
root_mean_prior_squared_error
0.3000000000000046
root_mean_squared_error
0.20371476930021723
root_relative_squared_error
0.6790492310007136
total_cost
0
area_under_roc_curve
0.9022083333333332 [0.999861,0.881111,0.935556,0.944306,0.825972,0.973194,0.771944,0.939722,0.999028,0.751389]
area_under_roc_curve
0.9073055555555556 [0.972083,0.853056,0.917083,0.944444,0.848056,0.910556,0.829306,0.96375,0.974028,0.860694]
area_under_roc_curve
0.8845694444444443 [1,0.927639,0.9225,0.836667,0.904444,0.890278,0.697361,0.9175,0.997222,0.752083]
area_under_roc_curve
0.9169166666666666 [1,0.776111,0.974028,0.972639,0.909444,0.944861,0.841667,0.886528,0.974722,0.889167]
area_under_roc_curve
0.8911805555555555 [0.997222,0.7475,0.97125,0.939306,0.872361,0.85625,0.856111,0.946667,0.971528,0.753611]
area_under_roc_curve
0.919888888888889 [1,0.963611,0.996806,0.890972,0.908194,0.915972,0.835972,0.965556,0.999583,0.722222]
area_under_roc_curve
0.9000277777777778 [1,0.89625,0.896389,0.888194,0.870694,0.908889,0.782917,0.988472,0.99875,0.769722]
area_under_roc_curve
0.8886111111111111 [0.974583,0.848056,0.915278,0.906111,0.771806,0.942778,0.809861,0.962361,0.944722,0.810556]
area_under_roc_curve
0.9136666666666667 [1,0.788056,0.989306,0.971667,0.875278,0.917917,0.772361,0.986667,1,0.835417]
area_under_roc_curve
0.8886527777777777 [0.994444,0.83125,0.944167,0.890972,0.853056,0.948611,0.759722,0.978056,0.942917,0.743333]
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
0.7572856661239205 [0.97561,0.714286,0.772727,0.85,0.666667,0.947368,0.5,0.777778,0.947368,0.421053]
f_measure
0.7436868798707245 [0.926829,0.666667,0.833333,0.9,0.588235,0.744186,0.521739,0.808511,0.947368,0.5]
f_measure
0.7340063742389324 [1,0.714286,0.918919,0.666667,0.744186,0.777778,0.409091,0.756757,0.952381,0.4]
f_measure
0.8005025421537049 [1,0.611111,0.95,0.883721,0.68,0.918919,0.611111,0.756757,0.974359,0.619048]
f_measure
0.7364977876316746 [0.97561,0.571429,0.888889,0.818182,0.666667,0.717949,0.52381,0.765957,0.95,0.486486]
f_measure
0.7752569699119763 [0.97561,0.809524,0.926829,0.810811,0.769231,0.829268,0.571429,0.8,0.947368,0.3125]
f_measure
0.7225262283640644 [0.97561,0.666667,0.789474,0.714286,0.594595,0.780488,0.511628,0.829268,0.974359,0.388889]
f_measure
0.7229719464541986 [0.974359,0.681818,0.8,0.714286,0.578947,0.85,0.511628,0.8,0.857143,0.461538]
f_measure
0.7689953593878355 [1,0.645161,0.904762,0.857143,0.666667,0.829268,0.457143,0.818182,1,0.511628]
f_measure
0.739117887684517 [0.952381,0.666667,0.857143,0.864865,0.666667,0.894737,0.468085,0.844444,0.833333,0.342857]
kappa
0.7277777777777777
kappa
0.7166666666666667
kappa
0.7
kappa
0.7777777777777778
kappa
0.7111111111111111
kappa
0.7555555555555555
kappa
0.6944444444444444
kappa
0.6888888888888889
kappa
0.75
kappa
0.7111111111111111
kb_relative_information_score
151.30748059535685
kb_relative_information_score
151.86052112132805
kb_relative_information_score
146.60619661558482
kb_relative_information_score
157.02185403839923
kb_relative_information_score
146.83557345417847
kb_relative_information_score
159.16586665595477
kb_relative_information_score
146.99529869922864
kb_relative_information_score
146.23023384908646
kb_relative_information_score
155.66716527368828
kb_relative_information_score
147.26729905502825
mean_absolute_error
0.05338888888888887
mean_absolute_error
0.05277222222222223
mean_absolute_error
0.05562936507936505
mean_absolute_error
0.04751785714285714
mean_absolute_error
0.05868571428571427
mean_absolute_error
0.04492579365079363
mean_absolute_error
0.056378571428571396
mean_absolute_error
0.05794484126984125
mean_absolute_error
0.047303968253968244
mean_absolute_error
0.05771785714285713
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
0.7654520771626036 [0.952381,0.681818,0.708333,0.85,0.684211,1,0.458333,0.875,1,0.444444]
precision
0.7564152484518618 [0.904762,0.684211,0.9375,0.9,0.714286,0.695652,0.461538,0.703704,1,0.5625]
precision
0.7444301202902629 [1,0.681818,1,0.684211,0.695652,0.875,0.375,0.823529,0.909091,0.4]
precision
0.8132192125862201 [1,0.6875,0.95,0.826087,0.566667,1,0.6875,0.823529,1,0.590909]
precision
0.7436178681999117 [0.952381,0.666667,1,0.75,0.684211,0.736842,0.5,0.666667,0.95,0.529412]
precision
0.7810645852137259 [0.952381,0.772727,0.904762,0.882353,0.789474,0.809524,0.482759,0.8,1,0.416667]
precision
0.7238144368419305 [0.952381,0.636364,0.833333,0.681818,0.647059,0.761905,0.478261,0.809524,1,0.4375]
precision
0.7319874373020826 [1,0.625,0.8,0.681818,0.611111,0.85,0.478261,0.8,1,0.473684]
precision
0.7798390739695087 [1,0.909091,0.863636,0.818182,0.636364,0.809524,0.533333,0.75,1,0.478261]
precision
0.750416468607645 [0.909091,0.75,0.818182,0.941176,0.636364,0.944444,0.407407,0.76,0.9375,0.4]
predictive_accuracy
0.755
predictive_accuracy
0.745
predictive_accuracy
0.73
predictive_accuracy
0.8
predictive_accuracy
0.74
predictive_accuracy
0.78
predictive_accuracy
0.725
predictive_accuracy
0.72
predictive_accuracy
0.775
predictive_accuracy
0.74
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
0.755 [1,0.75,0.85,0.85,0.65,0.9,0.55,0.7,0.9,0.4]
recall
0.745 [0.95,0.65,0.75,0.9,0.5,0.8,0.6,0.95,0.9,0.45]
recall
0.73 [1,0.75,0.85,0.65,0.8,0.7,0.45,0.7,1,0.4]
recall
0.8 [1,0.55,0.95,0.95,0.85,0.85,0.55,0.7,0.95,0.65]
recall
0.74 [1,0.5,0.8,0.9,0.65,0.7,0.55,0.9,0.95,0.45]
recall
0.78 [1,0.85,0.95,0.75,0.75,0.85,0.7,0.8,0.9,0.25]
recall
0.725 [1,0.7,0.75,0.75,0.55,0.8,0.55,0.85,0.95,0.35]
recall
0.72 [0.95,0.75,0.8,0.75,0.55,0.85,0.55,0.8,0.75,0.45]
recall
0.775 [1,0.5,0.95,0.9,0.7,0.85,0.4,0.9,1,0.55]
recall
0.74 [1,0.6,0.9,0.8,0.7,0.85,0.55,0.95,0.75,0.3]
relative_absolute_error
0.29660493827160517
relative_absolute_error
0.2931790123456794
relative_absolute_error
0.30905202821869504
relative_absolute_error
0.2639880952380955
relative_absolute_error
0.32603174603174634
relative_absolute_error
0.24958774250440935
relative_absolute_error
0.3132142857142859
relative_absolute_error
0.32191578483245176
relative_absolute_error
0.26279982363315724
relative_absolute_error
0.3206547619047623
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
0.20220265878058832
root_mean_squared_error
0.20196978072979715
root_mean_squared_error
0.2158022515463793
root_mean_squared_error
0.18806745659143956
root_mean_squared_error
0.21222781799498994
root_mean_squared_error
0.18792145084269354
root_mean_squared_error
0.20935155858479917
root_mean_squared_error
0.2137499154632446
root_mean_squared_error
0.19152515068766024
root_mean_squared_error
0.211719818526909
root_relative_squared_error
0.6740088626019615
root_relative_squared_error
0.6732326024326575
root_relative_squared_error
0.7193408384879314
root_relative_squared_error
0.6268915219714656
root_relative_squared_error
0.7074260599833002
root_relative_squared_error
0.6264048361423121
root_relative_squared_error
0.6978385286159977
root_relative_squared_error
0.7124997182108157
root_relative_squared_error
0.6384171689588679
root_relative_squared_error
0.7057327284230304
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
usercpu_time_millis
2314.440216996445
usercpu_time_millis
2326.178882001841
usercpu_time_millis
2386.0859960004746
usercpu_time_millis
2341.3532939994184
usercpu_time_millis
2340.948623001168
usercpu_time_millis
2347.633405999659
usercpu_time_millis
2360.9400119967177
usercpu_time_millis
2360.8676839976397
usercpu_time_millis
2324.5635139974183
usercpu_time_millis
2350.968129005196
usercpu_time_millis_testing
1.6799819968582597
usercpu_time_millis_testing
1.5218840017041657
usercpu_time_millis_testing
1.6720530002203304
usercpu_time_millis_testing
1.614153999980772
usercpu_time_millis_testing
1.5801650006324053
usercpu_time_millis_testing
1.6153090000443626
usercpu_time_millis_testing
1.5079549993970431
usercpu_time_millis_testing
1.5969099986250512
usercpu_time_millis_testing
1.7145769998023752
usercpu_time_millis_testing
1.625047003471991
usercpu_time_millis_training
2312.760234999587
usercpu_time_millis_training
2324.656998000137
usercpu_time_millis_training
2384.413943000254
usercpu_time_millis_training
2339.7391399994376
usercpu_time_millis_training
2339.3684580005356
usercpu_time_millis_training
2346.0180969996145
usercpu_time_millis_training
2359.4320569973206
usercpu_time_millis_training
2359.2707739990146
usercpu_time_millis_training
2322.848936997616
usercpu_time_millis_training
2349.343082001724