10145367
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)
8070971
axis
0
8778
copy
true
8778
missing_values
"NaN"
8778
strategy
"median"
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
13
8783
min_samples_split
9
8783
min_weight_fraction_leaf
0.0
8783
presort
false
8783
random_state
14941
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
21211273
description
https://api.openml.org/data/download/21211273/description.xml
-1
21211274
predictions
https://api.openml.org/data/download/21211274/predictions.arff
area_under_roc_curve
0.9379922222222222 [0.991453,0.91016,0.967528,0.937582,0.911014,0.951433,0.888083,0.973071,0.979804,0.869794]
average_cost
0
f_measure
0.7513846684110439 [0.955665,0.668224,0.895288,0.768116,0.688442,0.831169,0.49,0.835749,0.937343,0.44385]
kappa
0.725
kb_relative_information_score
1522.5487550169566
mean_absolute_error
0.05782338980052011
mean_prior_absolute_error
0.18000000000000554
number_of_instances
2000 [200,200,200,200,200,200,200,200,200,200]
precision
0.7523396907490234 [0.941748,0.627193,0.93956,0.742991,0.691919,0.864865,0.49,0.808411,0.939698,0.477011]
predictive_accuracy
0.7525
prior_entropy
3.321928094887362
recall
0.7525 [0.97,0.715,0.855,0.795,0.685,0.8,0.49,0.865,0.935,0.415]
relative_absolute_error
0.3212410544473241
root_mean_prior_squared_error
0.3000000000000046
root_mean_squared_error
0.1903390059538018
root_relative_squared_error
0.6344633531793296
total_cost
0
area_under_roc_curve
0.9405138888888891 [0.999861,0.9625,0.964444,0.90625,0.933333,0.994722,0.875972,0.967639,0.9975,0.802917]
area_under_roc_curve
0.9104722222222223 [0.974306,0.912222,0.918056,0.930833,0.823472,0.8975,0.842639,0.988056,0.948333,0.869306]
area_under_roc_curve
0.9328888888888889 [0.973889,0.897639,0.945139,0.869167,0.972361,0.992083,0.901667,0.945972,0.997083,0.833889]
area_under_roc_curve
0.9247500000000001 [0.996667,0.853056,0.971806,0.987361,0.914028,0.879444,0.832778,0.964861,0.974583,0.872917]
area_under_roc_curve
0.9376666666666666 [1,0.902917,0.966111,0.936111,0.948472,0.969444,0.895278,0.928889,0.996806,0.832639]
area_under_roc_curve
0.9400972222222223 [1,0.944167,0.998472,0.908333,0.885694,0.936389,0.891111,0.980556,0.99875,0.8575]
area_under_roc_curve
0.9541944444444443 [0.999722,0.895694,0.9475,0.960833,0.958472,0.977083,0.944444,0.98625,0.974722,0.897222]
area_under_roc_curve
0.9395555555555555 [0.973611,0.910833,0.999444,0.941667,0.839028,0.994028,0.921528,0.988194,0.945417,0.881806]
area_under_roc_curve
0.9666111111111111 [0.999722,0.892083,0.998333,0.990833,0.95625,0.942778,0.956806,0.990556,1,0.93875]
area_under_roc_curve
0.9374583333333333 [0.996389,0.940417,0.968333,0.940833,0.889583,0.938472,0.819861,0.995833,0.969306,0.915556]
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
0.740484085230834 [0.97561,0.652174,0.842105,0.820513,0.790698,0.923077,0.439024,0.789474,0.878049,0.294118]
f_measure
0.7018356021106977 [0.974359,0.697674,0.833333,0.780488,0.585366,0.648649,0.193548,0.829268,0.947368,0.528302]
f_measure
0.7328552095521478 [0.95,0.638298,0.918919,0.666667,0.755556,0.878049,0.409091,0.833333,0.97561,0.30303]
f_measure
0.7555664425240027 [0.904762,0.604651,0.923077,0.826087,0.634146,0.777778,0.571429,0.810811,0.947368,0.555556]
f_measure
0.7137760664458831 [0.97561,0.595745,0.888889,0.736842,0.619048,0.864865,0.363636,0.727273,0.97561,0.390244]
f_measure
0.7702847437504792 [0.97561,0.782609,0.947368,0.790698,0.628571,0.857143,0.484848,0.790698,0.904762,0.540541]
f_measure
0.7810601303458446 [0.974359,0.666667,0.923077,0.761905,0.75,0.761905,0.734694,0.863636,0.974359,0.4]
f_measure
0.7537603366673133 [0.95,0.651163,0.9,0.651163,0.628571,0.9,0.564103,0.863636,0.864865,0.564103]
f_measure
0.8025867780160449 [0.95,0.702703,0.894737,0.826087,0.8,0.823529,0.585366,0.888889,0.97561,0.578947]
f_measure
0.7326373187544306 [0.930233,0.7,0.878049,0.8,0.666667,0.864865,0.425532,0.952381,0.926829,0.181818]
kappa
0.7166666666666667
kappa
0.6722222222222222
kappa
0.7055555555555556
kappa
0.7277777777777777
kappa
0.6833333333333333
kappa
0.7555555555555555
kappa
0.7666666666666667
kappa
0.7277777777777777
kappa
0.7833333333333334
kappa
0.7111111111111111
kb_relative_information_score
153.28108790125316
kb_relative_information_score
143.51378936123803
kb_relative_information_score
149.90681874429274
kb_relative_information_score
149.90967294070984
kb_relative_information_score
149.54949926759903
kb_relative_information_score
153.7072489424372
kb_relative_information_score
158.48158488355548
kb_relative_information_score
152.1525594901174
kb_relative_information_score
163.27908652950208
kb_relative_information_score
148.76740695626665
mean_absolute_error
0.055481099626282664
mean_absolute_error
0.06627355337077025
mean_absolute_error
0.059871176065450483
mean_absolute_error
0.05864199649679521
mean_absolute_error
0.060358628515447356
mean_absolute_error
0.05673687627873684
mean_absolute_error
0.0514286434021849
mean_absolute_error
0.05899971341269964
mean_absolute_error
0.048737183725885064
mean_absolute_error
0.06170502711094412
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
0.7422987513376529 [0.952381,0.576923,0.888889,0.842105,0.73913,0.947368,0.428571,0.833333,0.857143,0.357143]
precision
0.7135383105811496 [1,0.652174,0.9375,0.761905,0.571429,0.705882,0.272727,0.809524,1,0.424242]
precision
0.7442194749694748 [0.95,0.555556,1,0.75,0.68,0.857143,0.375,0.9375,0.952381,0.384615]
precision
0.7653846512441208 [0.863636,0.565217,0.947368,0.730769,0.619048,0.875,0.545455,0.882353,1,0.625]
precision
0.7242301271713036 [0.952381,0.518519,1,0.777778,0.590909,0.941176,0.461538,0.666667,0.952381,0.380952]
precision
0.7741720938907639 [0.952381,0.692308,1,0.73913,0.733333,0.818182,0.615385,0.73913,0.863636,0.588235]
precision
0.7914270197437167 [1,0.75,0.947368,0.727273,0.75,0.727273,0.62069,0.791667,1,0.6]
precision
0.7591462511778166 [0.95,0.608696,0.9,0.608696,0.733333,0.9,0.578947,0.791667,0.941176,0.578947]
precision
0.8124840192487252 [0.95,0.764706,0.944444,0.730769,0.8,1,0.571429,0.8,0.952381,0.611111]
precision
0.7332876960114812 [0.869565,0.7,0.857143,0.8,0.75,0.941176,0.37037,0.909091,0.904762,0.230769]
predictive_accuracy
0.745
predictive_accuracy
0.705
predictive_accuracy
0.735
predictive_accuracy
0.755
predictive_accuracy
0.715
predictive_accuracy
0.78
predictive_accuracy
0.79
predictive_accuracy
0.755
predictive_accuracy
0.805
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
0.745 [1,0.75,0.8,0.8,0.85,0.9,0.45,0.75,0.9,0.25]
recall
0.705 [0.95,0.75,0.75,0.8,0.6,0.6,0.15,0.85,0.9,0.7]
recall
0.735 [0.95,0.75,0.85,0.6,0.85,0.9,0.45,0.75,1,0.25]
recall
0.755 [0.95,0.65,0.9,0.95,0.65,0.7,0.6,0.75,0.9,0.5]
recall
0.715 [1,0.7,0.8,0.7,0.65,0.8,0.3,0.8,1,0.4]
recall
0.78 [1,0.9,0.9,0.85,0.55,0.9,0.4,0.85,0.95,0.5]
recall
0.79 [0.95,0.6,0.9,0.8,0.75,0.8,0.9,0.95,0.95,0.3]
recall
0.755 [0.95,0.7,0.9,0.7,0.55,0.9,0.55,0.95,0.8,0.55]
recall
0.805 [0.95,0.65,0.85,0.95,0.8,0.7,0.6,1,1,0.55]
recall
0.74 [1,0.7,0.9,0.8,0.6,0.8,0.5,1,0.95,0.15]
relative_absolute_error
0.30822833125712623
relative_absolute_error
0.3681864076153907
relative_absolute_error
0.3326176448080586
relative_absolute_error
0.3257888694266404
relative_absolute_error
0.3353257139747079
relative_absolute_error
0.315204868215205
relative_absolute_error
0.2857146855676942
relative_absolute_error
0.32777618562610944
relative_absolute_error
0.2707621318104729
relative_absolute_error
0.34280570617191214
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
0.19060417870413382
root_mean_squared_error
0.21155737770868407
root_mean_squared_error
0.19305326339162593
root_mean_squared_error
0.19591799068317392
root_mean_squared_error
0.19666830891515447
root_mean_squared_error
0.1847087882042209
root_mean_squared_error
0.1774034655838852
root_mean_squared_error
0.18910141647346465
root_mean_squared_error
0.16357082351324367
root_mean_squared_error
0.19689327947700608
root_relative_squared_error
0.635347262347113
root_relative_squared_error
0.7051912590289473
root_relative_squared_error
0.643510877972087
root_relative_squared_error
0.6530599689439134
root_relative_squared_error
0.6555610297171819
root_relative_squared_error
0.6156959606807367
root_relative_squared_error
0.5913448852796177
root_relative_squared_error
0.6303380549115492
root_relative_squared_error
0.5452360783774793
root_relative_squared_error
0.6563109315900206
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
665.854977996787
usercpu_time_millis
501.08796000131406
usercpu_time_millis
491.19728799996665
usercpu_time_millis
490.044673999364
usercpu_time_millis
487.02474600213463
usercpu_time_millis
456.682184998499
usercpu_time_millis
476.53690399965853
usercpu_time_millis
480.5767329999071
usercpu_time_millis
451.96630300051766
usercpu_time_millis
456.4881080004852
usercpu_time_millis_testing
1.797140997950919
usercpu_time_millis_testing
1.378925000608433
usercpu_time_millis_testing
1.3692680004169233
usercpu_time_millis_testing
1.4911220023350324
usercpu_time_millis_testing
1.3844780005456414
usercpu_time_millis_testing
1.3083679987175856
usercpu_time_millis_testing
1.3151170023775194
usercpu_time_millis_testing
1.3030299996898975
usercpu_time_millis_testing
1.338281999778701
usercpu_time_millis_testing
1.3087500010442454
usercpu_time_millis_training
664.0578369988361
usercpu_time_millis_training
499.7090350007056
usercpu_time_millis_training
489.8280199995497
usercpu_time_millis_training
488.553551997029
usercpu_time_millis_training
485.640268001589
usercpu_time_millis_training
455.3738169997814
usercpu_time_millis_training
475.221786997281
usercpu_time_millis_training
479.2737030002172
usercpu_time_millis_training
450.62802100073895
usercpu_time_millis_training
455.179357999441