Run
9804156

Run 9804156

Task 9955 (Supervised Classification) one-hundred-plants-shape Uploaded 22-10-2018 by Scikit-learn Bot
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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,svc=sklearn.svm.classes.SVC)(1)Automatically created scikit-learn flow.
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sklearn.preprocessing.imputation.Imputer(29)_verbose0
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sklearn.preprocessing.data.StandardScaler(14)_with_meantrue
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sklearn.preprocessing._encoders.OneHotEncoder(3)_sparsetrue
sklearn.svm.classes.SVC(22)_C704.8169210527047
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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"
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sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler)(1)_memorynull
sklearn.feature_selection.variance_threshold.VarianceThreshold(18)_threshold0.0
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,svc=sklearn.svm.classes.SVC)(1)_memorynull

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
0.7721 ± 0.0134
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.532
Per class
Kappa
0.5442 ± 0.0269
Cross-validation details (10-fold Crossvalidation)
KB relative information score
876.4243 ± 4.2728
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.009 ± 0.0005
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.0198
Cross-validation details (10-fold Crossvalidation)
Number of instances
1600
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.5663
Per class
Predictive accuracy
0.5488 ± 0.0266
Cross-validation details (10-fold Crossvalidation)
Prior entropy
6.6439
Cross-validation details (10-fold Crossvalidation)
Recall
0.5488 ± 0.0266
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.4558 ± 0.0269
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.0995
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.095 ± 0.0028
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9548 ± 0.028
Cross-validation details (10-fold Crossvalidation)