10149306
1
Jan van Rijn
9976
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)
8074940
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
18
8783
min_samples_split
8
8783
min_weight_fraction_leaf
0.0
8783
presort
false
8783
random_state
50539
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.
1485
madelon
https://www.openml.org/data/download/1590986/phpfLuQE4
-1
21219151
description
https://api.openml.org/data/download/21219151/description.xml
-1
21219152
predictions
https://api.openml.org/data/download/21219152/predictions.arff
area_under_roc_curve
0.8289742603550296 [0.828974,0.828974]
average_cost
0
f_measure
0.7572918588328025 [0.759252,0.755332]
kappa
0.5146153846153847
kb_relative_information_score
1246.3261128362772
mean_absolute_error
0.264134475916909
mean_prior_absolute_error
0.5
number_of_instances
2600 [1300,1300]
precision
0.7573748534380865 [0.753217,0.761532]
predictive_accuracy
0.7573076923076922
prior_entropy
1
recall
0.7573076923076923 [0.765385,0.749231]
relative_absolute_error
0.528268951833818
root_mean_prior_squared_error
0.5
root_mean_squared_error
0.4237147498554429
root_relative_squared_error
0.8474294997108858
total_cost
0
area_under_roc_curve
0.862869822485207 [0.86287,0.86287]
area_under_roc_curve
0.8190236686390533 [0.819024,0.819024]
area_under_roc_curve
0.8346153846153846 [0.834615,0.834615]
area_under_roc_curve
0.8361242603550296 [0.836124,0.836124]
area_under_roc_curve
0.8372485207100592 [0.837249,0.837249]
area_under_roc_curve
0.8221597633136095 [0.82216,0.82216]
area_under_roc_curve
0.8573076923076923 [0.857308,0.857308]
area_under_roc_curve
0.7673372781065089 [0.767337,0.767337]
area_under_roc_curve
0.7967455621301776 [0.796746,0.796746]
area_under_roc_curve
0.8521005917159763 [0.852101,0.852101]
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
0.7807659876625392 [0.781609,0.779923]
f_measure
0.7846026392094209 [0.782946,0.78626]
f_measure
0.7495517123845937 [0.738956,0.760148]
f_measure
0.7652978172401036 [0.760784,0.769811]
f_measure
0.7422733795919575 [0.745247,0.7393]
f_measure
0.7461388247825315 [0.744186,0.748092]
f_measure
0.8153736907509319 [0.813953,0.816794]
f_measure
0.6834164884770729 [0.702899,0.663934]
f_measure
0.740924166034593 [0.759857,0.721992]
f_measure
0.7614820075757577 [0.765152,0.757813]
kappa
0.5615384615384615
kappa
0.5692307692307692
kappa
0.5
kappa
0.5307692307692307
kappa
0.48461538461538467
kappa
0.49230769230769234
kappa
0.6307692307692307
kappa
0.36923076923076925
kappa
0.48461538461538467
kappa
0.523076923076923
kb_relative_information_score
136.68791004886648
kb_relative_information_score
126.63984442392584
kb_relative_information_score
124.47798419951044
kb_relative_information_score
133.88347283826698
kb_relative_information_score
125.76190427927455
kb_relative_information_score
121.86812836101521
kb_relative_information_score
140.50383671468373
kb_relative_information_score
92.1567412247606
kb_relative_information_score
111.38232822333026
kb_relative_information_score
132.96396252264253
mean_absolute_error
0.23991967943737702
mean_absolute_error
0.2632418834965033
mean_absolute_error
0.26392191672564297
mean_absolute_error
0.24631807000850214
mean_absolute_error
0.261526812709691
mean_absolute_error
0.2681497085944705
mean_absolute_error
0.23594799304565672
mean_absolute_error
0.32564333524248434
mean_absolute_error
0.28983122224806407
mean_absolute_error
0.2468441376607095
mean_prior_absolute_error
0.5
mean_prior_absolute_error
0.5
mean_prior_absolute_error
0.5
mean_prior_absolute_error
0.5
mean_prior_absolute_error
0.5
mean_prior_absolute_error
0.5
mean_prior_absolute_error
0.5
mean_prior_absolute_error
0.5
mean_prior_absolute_error
0.5
mean_prior_absolute_error
0.5
number_of_instances
260 [130,130]
number_of_instances
260 [130,130]
number_of_instances
260 [130,130]
number_of_instances
260 [130,130]
number_of_instances
260 [130,130]
number_of_instances
260 [130,130]
number_of_instances
260 [130,130]
number_of_instances
260 [130,130]
number_of_instances
260 [130,130]
number_of_instances
260 [130,130]
precision
0.7807858453162909 [0.778626,0.782946]
precision
0.7846827651515151 [0.789062,0.780303]
precision
0.7518028487990941 [0.773109,0.730496]
precision
0.7657777777777778 [0.776,0.755556]
precision
0.742436800663075 [0.736842,0.748031]
precision
0.7462121212121211 [0.75,0.742424]
precision
0.8154592803030303 [0.820312,0.810606]
precision
0.6874549387166546 [0.664384,0.710526]
precision
0.7475965898784691 [0.711409,0.783784]
precision
0.761786306562426 [0.753731,0.769841]
predictive_accuracy
0.7807692307692308
predictive_accuracy
0.7846153846153847
predictive_accuracy
0.75
predictive_accuracy
0.7653846153846153
predictive_accuracy
0.7423076923076922
predictive_accuracy
0.7461538461538462
predictive_accuracy
0.8153846153846154
predictive_accuracy
0.6846153846153846
predictive_accuracy
0.7423076923076922
predictive_accuracy
0.7615384615384616
prior_entropy
1
prior_entropy
1
prior_entropy
1
prior_entropy
1
prior_entropy
1
prior_entropy
1
prior_entropy
1
prior_entropy
1
prior_entropy
1
prior_entropy
1
recall
0.7807692307692308 [0.784615,0.776923]
recall
0.7846153846153846 [0.776923,0.792308]
recall
0.75 [0.707692,0.792308]
recall
0.7653846153846153 [0.746154,0.784615]
recall
0.7423076923076923 [0.753846,0.730769]
recall
0.7461538461538462 [0.738462,0.753846]
recall
0.8153846153846154 [0.807692,0.823077]
recall
0.6846153846153846 [0.746154,0.623077]
recall
0.7423076923076923 [0.815385,0.669231]
recall
0.7615384615384615 [0.776923,0.746154]
relative_absolute_error
0.47983935887475404
relative_absolute_error
0.5264837669930066
relative_absolute_error
0.5278438334512859
relative_absolute_error
0.49263614001700434
relative_absolute_error
0.523053625419382
relative_absolute_error
0.536299417188941
relative_absolute_error
0.47189598609131345
relative_absolute_error
0.6512866704849687
relative_absolute_error
0.5796624444961281
relative_absolute_error
0.493688275321419
root_mean_prior_squared_error
0.5
root_mean_prior_squared_error
0.5
root_mean_prior_squared_error
0.5
root_mean_prior_squared_error
0.5
root_mean_prior_squared_error
0.5
root_mean_prior_squared_error
0.5
root_mean_prior_squared_error
0.5
root_mean_prior_squared_error
0.5
root_mean_prior_squared_error
0.5
root_mean_prior_squared_error
0.5
root_mean_squared_error
0.3958162808923427
root_mean_squared_error
0.42269963870676347
root_mean_squared_error
0.42446343870418624
root_mean_squared_error
0.40534194501953746
root_mean_squared_error
0.4157187039533587
root_mean_squared_error
0.4405869786412623
root_mean_squared_error
0.3923048369602668
root_mean_squared_error
0.47124268993389934
root_mean_squared_error
0.45282433484874496
root_mean_squared_error
0.4093452256529485
root_relative_squared_error
0.7916325617846854
root_relative_squared_error
0.8453992774135269
root_relative_squared_error
0.8489268774083725
root_relative_squared_error
0.8106838900390749
root_relative_squared_error
0.8314374079067174
root_relative_squared_error
0.8811739572825246
root_relative_squared_error
0.7846096739205336
root_relative_squared_error
0.9424853798677987
root_relative_squared_error
0.9056486696974899
root_relative_squared_error
0.818690451305897
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
902.4750019998464
usercpu_time_millis
843.2080009988567
usercpu_time_millis
846.3550360011141
usercpu_time_millis
773.6249090012279
usercpu_time_millis
732.3144089987181
usercpu_time_millis
750.8081610012596
usercpu_time_millis
775.8749050008191
usercpu_time_millis
790.0334330006444
usercpu_time_millis
776.4758350022021
usercpu_time_millis
789.9554560008255
usercpu_time_millis_testing
5.660511000314727
usercpu_time_millis_testing
5.723591999412747
usercpu_time_millis_testing
5.3661250003642635
usercpu_time_millis_testing
5.688317000021925
usercpu_time_millis_testing
5.023245999836945
usercpu_time_millis_testing
5.041086000346695
usercpu_time_millis_testing
5.027385001085349
usercpu_time_millis_testing
5.057458000010229
usercpu_time_millis_testing
5.416645000877907
usercpu_time_millis_testing
5.099993000840186
usercpu_time_millis_training
896.8144909995317
usercpu_time_millis_training
837.484408999444
usercpu_time_millis_training
840.9889110007498
usercpu_time_millis_training
767.936592001206
usercpu_time_millis_training
727.2911629988812
usercpu_time_millis_training
745.7670750009129
usercpu_time_millis_training
770.8475199997338
usercpu_time_millis_training
784.9759750006342
usercpu_time_millis_training
771.0591900013242
usercpu_time_millis_training
784.8554629999853