Run
10125290

Run 10125290

Task 125920 (Supervised Classification) dresses-sales Uploaded 25-01-2019 by Jan van Rijn
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Flow

sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transfo rmer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.pr eprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.St andardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.imput e.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder )),variancethreshold=sklearn.feature_selection.variance_threshold.VarianceT hreshold,decisiontreeclassifier=sklearn.tree.tree.DecisionTreeClassifier)(1 )Automatically created scikit-learn flow.
sklearn.preprocessing.imputation.Imputer(29)_axis0
sklearn.preprocessing.imputation.Imputer(29)_copytrue
sklearn.preprocessing.imputation.Imputer(29)_missing_values"NaN"
sklearn.preprocessing.imputation.Imputer(29)_strategy"mean"
sklearn.preprocessing.imputation.Imputer(29)_verbose0
sklearn.preprocessing.data.StandardScaler(14)_copytrue
sklearn.preprocessing.data.StandardScaler(14)_with_meantrue
sklearn.preprocessing.data.StandardScaler(14)_with_stdtrue
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)(1)_memorynull
sklearn.impute.SimpleImputer(1)_copytrue
sklearn.impute.SimpleImputer(1)_fill_value-1
sklearn.impute.SimpleImputer(1)_missing_valuesNaN
sklearn.impute.SimpleImputer(1)_strategy"constant"
sklearn.impute.SimpleImputer(1)_verbose0
sklearn.preprocessing._encoders.OneHotEncoder(3)_categorical_featuresnull
sklearn.preprocessing._encoders.OneHotEncoder(3)_categoriesnull
sklearn.preprocessing._encoders.OneHotEncoder(3)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing._encoders.OneHotEncoder(3)_handle_unknown"ignore"
sklearn.preprocessing._encoders.OneHotEncoder(3)_n_valuesnull
sklearn.preprocessing._encoders.OneHotEncoder(3)_sparsetrue
sklearn.tree.tree.DecisionTreeClassifier(29)_class_weightnull
sklearn.tree.tree.DecisionTreeClassifier(29)_criterion"entropy"
sklearn.tree.tree.DecisionTreeClassifier(29)_max_depthnull
sklearn.tree.tree.DecisionTreeClassifier(29)_max_features1.0
sklearn.tree.tree.DecisionTreeClassifier(29)_max_leaf_nodesnull
sklearn.tree.tree.DecisionTreeClassifier(29)_min_impurity_decrease0.0
sklearn.tree.tree.DecisionTreeClassifier(29)_min_impurity_splitnull
sklearn.tree.tree.DecisionTreeClassifier(29)_min_samples_leaf18
sklearn.tree.tree.DecisionTreeClassifier(29)_min_samples_split14
sklearn.tree.tree.DecisionTreeClassifier(29)_min_weight_fraction_leaf0.0
sklearn.tree.tree.DecisionTreeClassifier(29)_presortfalse
sklearn.tree.tree.DecisionTreeClassifier(29)_random_state45325
sklearn.tree.tree.DecisionTreeClassifier(29)_splitter"best"
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))(1)_n_jobsnull
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))(1)_remainder"passthrough"
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))(1)_sparse_threshold0.3
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))(1)_transformer_weightsnull
sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler)(1)_memorynull
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)_memorynull
sklearn.feature_selection.variance_threshold.VarianceThreshold(18)_threshold0.0

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

17 Evaluation measures

Area under ROC curve
0.6073 ± 0.06
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.5836 ± 0.0545
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.1398 ± 0.1113
Cross-validation details (10-fold Crossvalidation)
KB relative information score
42.0359 ± 2.2808
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.4482 ± 0.019
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4873
Cross-validation details (10-fold Crossvalidation)
Number of instances
500
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.5822 ± 0.0604
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.59 ± 0.0583
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9816
Cross-validation details (10-fold Crossvalidation)
Recall
0.59 ± 0.0583
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.9199 ± 0.0389
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4936
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.5031 ± 0.017
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.0194 ± 0.0344
Cross-validation details (10-fold Crossvalidation)