10100363
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)
8025535
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
"entropy"
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
11
8783
min_samples_split
2
8783
min_weight_fraction_leaf
0.0
8783
presort
false
8783
random_state
21087
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
21121264
description
https://api.openml.org/data/download/21121264/description.xml
-1
21121265
predictions
https://api.openml.org/data/download/21121265/predictions.arff
area_under_roc_curve
0.9336388888888888 [0.988282,0.880599,0.967389,0.942475,0.917372,0.948074,0.867079,0.975665,0.975165,0.874289]
average_cost
0
f_measure
0.7588298294313683 [0.957179,0.685579,0.898172,0.80292,0.691358,0.841026,0.471795,0.836983,0.933002,0.470284]
kappa
0.7327777777777778
kb_relative_information_score
1534.7056915324583
mean_absolute_error
0.05554578850844741
mean_prior_absolute_error
0.18000000000000554
number_of_instances
2000 [200,200,200,200,200,200,200,200,200,200]
precision
0.75947729695575 [0.964467,0.650224,0.939891,0.781991,0.682927,0.863158,0.484211,0.815166,0.926108,0.486631]
predictive_accuracy
0.7595000000000001
prior_entropy
3.321928094887362
recall
0.7595 [0.95,0.725,0.86,0.825,0.7,0.82,0.46,0.86,0.94,0.455]
relative_absolute_error
0.3085877139358094
root_mean_prior_squared_error
0.3000000000000046
root_mean_squared_error
0.18949185074640765
root_relative_squared_error
0.6316395024880158
total_cost
0
area_under_roc_curve
0.9361111111111111 [0.996944,0.919167,0.965694,0.912361,0.933472,0.968056,0.860417,0.989583,0.997917,0.8175]
area_under_roc_curve
0.9099861111111112 [0.971389,0.912361,0.917778,0.903194,0.820694,0.895833,0.876111,0.988472,0.948056,0.865972]
area_under_roc_curve
0.9462222222222223 [0.998611,0.875417,0.945972,0.933611,0.983472,0.99125,0.891111,0.946806,0.999722,0.89625]
area_under_roc_curve
0.9294444444444445 [0.97375,0.873472,0.968889,0.986806,0.942917,0.884028,0.837639,0.968333,0.949444,0.909167]
area_under_roc_curve
0.9206111111111112 [0.997083,0.846111,0.967222,0.911111,0.924167,0.945278,0.870972,0.929028,0.996667,0.818472]
area_under_roc_curve
0.9518055555555556 [1,0.939167,0.998472,0.963333,0.938056,0.937222,0.878333,0.990417,0.999028,0.874028]
area_under_roc_curve
0.9413611111111112 [0.999583,0.896944,0.947639,0.938056,0.959167,0.980972,0.883333,0.989028,0.974583,0.844306]
area_under_roc_curve
0.9205277777777777 [0.97125,0.807083,0.999444,0.947361,0.818889,0.994306,0.875694,0.985556,0.919583,0.886111]
area_under_roc_curve
0.9477500000000001 [0.974444,0.813889,0.995972,0.985,0.953056,0.915972,0.911528,0.984167,1,0.943472]
area_under_roc_curve
0.9342777777777779 [0.999583,0.927361,0.969028,0.941389,0.900278,0.97,0.783611,0.991389,0.969444,0.890694]
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
0.7551648389774193 [0.97561,0.666667,0.842105,0.820513,0.731707,0.923077,0.439024,0.820513,0.9,0.432432]
f_measure
0.6974408861219312 [0.894737,0.697674,0.864865,0.761905,0.571429,0.648649,0.206897,0.871795,0.947368,0.509091]
f_measure
0.744211302078162 [0.918919,0.666667,0.918919,0.820513,0.791667,0.837209,0.454545,0.8,0.97561,0.258065]
f_measure
0.7861223918112533 [0.974359,0.682927,0.923077,0.851064,0.711111,0.777778,0.604651,0.833333,0.947368,0.555556]
f_measure
0.7320009509255354 [0.97561,0.615385,0.888889,0.756757,0.615385,0.9,0.461538,0.765957,0.930233,0.410256]
f_measure
0.7458942592317119 [1,0.708333,0.947368,0.837209,0.647059,0.857143,0.275862,0.844444,0.909091,0.432432]
f_measure
0.795165278348847 [0.974359,0.736842,0.923077,0.810811,0.761905,0.829268,0.590909,0.863636,0.974359,0.486486]
f_measure
0.7450470374444165 [0.95,0.636364,0.9,0.682927,0.628571,0.926829,0.424242,0.837209,0.842105,0.622222]
f_measure
0.8071880621631269 [0.974359,0.684211,0.894737,0.826087,0.731707,0.764706,0.682927,0.888889,0.97561,0.648649]
f_measure
0.7460206234535246 [0.930233,0.761905,0.878049,0.85,0.684211,0.918919,0.425532,0.842105,0.926829,0.242424]
kappa
0.7277777777777777
kappa
0.6666666666666666
kappa
0.7222222222222222
kappa
0.7611111111111112
kappa
0.7055555555555556
kappa
0.7388888888888889
kappa
0.7722222222222223
kappa
0.7222222222222222
kappa
0.788888888888889
kappa
0.7222222222222222
kb_relative_information_score
154.01215083289352
kb_relative_information_score
142.74632318166124
kb_relative_information_score
155.8176214251169
kb_relative_information_score
155.75369699334652
kb_relative_information_score
151.7255553036208
kb_relative_information_score
152.89690887140142
kb_relative_information_score
157.0509563551225
kb_relative_information_score
151.35278166563842
kb_relative_information_score
160.262120500095
kb_relative_information_score
153.0875764035838
mean_absolute_error
0.05374903795035371
mean_absolute_error
0.06603429417160062
mean_absolute_error
0.05316039197730373
mean_absolute_error
0.053122223815915776
mean_absolute_error
0.05648762434675745
mean_absolute_error
0.056718533676505756
mean_absolute_error
0.0519740711086299
mean_absolute_error
0.05786460032485571
mean_absolute_error
0.04974679666738489
mean_absolute_error
0.056600311045163984
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
0.7586294166789521 [0.952381,0.6,0.888889,0.842105,0.714286,0.947368,0.428571,0.842105,0.9,0.470588]
precision
0.7144474629183205 [0.944444,0.652174,0.941176,0.727273,0.545455,0.705882,0.333333,0.894737,1,0.4]
precision
0.7569302703398813 [1,0.6,1,0.842105,0.678571,0.782609,0.416667,0.933333,0.952381,0.363636]
precision
0.7997493219764386 [1,0.666667,0.947368,0.740741,0.64,0.875,0.565217,0.9375,1,0.625]
precision
0.7370036985045735 [0.952381,0.631579,1,0.823529,0.631579,0.9,0.473684,0.666667,0.869565,0.421053]
precision
0.7502013669763029 [1,0.607143,1,0.782609,0.785714,0.818182,0.444444,0.76,0.833333,0.470588]
precision
0.8007040774842632 [1,0.777778,0.947368,0.882353,0.727273,0.809524,0.541667,0.791667,1,0.529412]
precision
0.750805436109784 [0.95,0.583333,0.9,0.666667,0.733333,0.904762,0.538462,0.782609,0.888889,0.56]
precision
0.8165223012281835 [1,0.722222,0.944444,0.730769,0.714286,0.928571,0.666667,0.8,0.952381,0.705882]
precision
0.7497916495742584 [0.869565,0.727273,0.857143,0.85,0.722222,1,0.37037,0.888889,0.904762,0.307692]
predictive_accuracy
0.755
predictive_accuracy
0.7
predictive_accuracy
0.75
predictive_accuracy
0.785
predictive_accuracy
0.735
predictive_accuracy
0.765
predictive_accuracy
0.795
predictive_accuracy
0.75
predictive_accuracy
0.81
predictive_accuracy
0.75
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 [1,0.75,0.8,0.8,0.75,0.9,0.45,0.8,0.9,0.4]
recall
0.7 [0.85,0.75,0.8,0.8,0.6,0.6,0.15,0.85,0.9,0.7]
recall
0.75 [0.85,0.75,0.85,0.8,0.95,0.9,0.5,0.7,1,0.2]
recall
0.785 [0.95,0.7,0.9,1,0.8,0.7,0.65,0.75,0.9,0.5]
recall
0.735 [1,0.6,0.8,0.7,0.6,0.9,0.45,0.9,1,0.4]
recall
0.765 [1,0.85,0.9,0.9,0.55,0.9,0.2,0.95,1,0.4]
recall
0.795 [0.95,0.7,0.9,0.75,0.8,0.85,0.65,0.95,0.95,0.45]
recall
0.75 [0.95,0.7,0.9,0.7,0.55,0.95,0.35,0.9,0.8,0.7]
recall
0.81 [0.95,0.65,0.85,0.95,0.75,0.65,0.7,1,1,0.6]
recall
0.75 [1,0.8,0.9,0.85,0.65,0.85,0.5,0.8,0.95,0.2]
relative_absolute_error
0.2986057663908543
relative_absolute_error
0.36685718984222604
relative_absolute_error
0.2953355109850211
relative_absolute_error
0.29512346564397685
relative_absolute_error
0.31382013525976393
relative_absolute_error
0.31510296486947675
relative_absolute_error
0.28874483949238866
relative_absolute_error
0.3214700018047543
relative_absolute_error
0.27637109259658305
relative_absolute_error
0.3144461724731336
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
0.19080724079128847
root_mean_squared_error
0.21364845673691585
root_mean_squared_error
0.18160582864019592
root_mean_squared_error
0.18569963441261028
root_mean_squared_error
0.1953371162780934
root_mean_squared_error
0.18452305838207972
root_mean_squared_error
0.1820409198392481
root_mean_squared_error
0.1956053715600381
root_mean_squared_error
0.17348412980621924
root_mean_squared_error
0.18934378343972474
root_relative_squared_error
0.6360241359709619
root_relative_squared_error
0.7121615224563865
root_relative_squared_error
0.6053527621339867
root_relative_squared_error
0.6189987813753679
root_relative_squared_error
0.6511237209269783
root_relative_squared_error
0.6150768612735995
root_relative_squared_error
0.6068030661308275
root_relative_squared_error
0.6520179052001274
root_relative_squared_error
0.5782804326873978
root_relative_squared_error
0.6311459447990829
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
2545.5319040001996
usercpu_time_millis
2269.3275789997642
usercpu_time_millis
2314.1698839999663
usercpu_time_millis
2544.1870940003355
usercpu_time_millis
2563.0373350004447
usercpu_time_millis
2364.109274999464
usercpu_time_millis
2307.6736630000596
usercpu_time_millis
2303.8753470009397
usercpu_time_millis
2281.4533450000454
usercpu_time_millis
2271.6795890000867
usercpu_time_millis_testing
1.3102169996273005
usercpu_time_millis_testing
1.3091860000713496
usercpu_time_millis_testing
1.3013859997954569
usercpu_time_millis_testing
1.654656999562576
usercpu_time_millis_testing
1.4375159998962772
usercpu_time_millis_testing
1.3014460000704275
usercpu_time_millis_testing
1.3091000000713393
usercpu_time_millis_testing
1.2947080003868905
usercpu_time_millis_testing
1.3468739998643287
usercpu_time_millis_testing
1.306434999605699
usercpu_time_millis_training
2544.2216870005723
usercpu_time_millis_training
2268.018392999693
usercpu_time_millis_training
2312.868498000171
usercpu_time_millis_training
2542.532437000773
usercpu_time_millis_training
2561.5998190005485
usercpu_time_millis_training
2362.8078289993937
usercpu_time_millis_training
2306.3645629999883
usercpu_time_millis_training
2302.5806390005528
usercpu_time_millis_training
2280.106471000181
usercpu_time_millis_training
2270.373154000481