Run
8857794

Run 8857794

Task 59 (Supervised Classification) iris Uploaded 10-02-2018 by Jan van Rijn
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Flow

sklearn.pipeline.Pipeline(Imputer=sklearn.preprocessing.imputation.Imputer, OneHotEncoder=sklearn.preprocessing.data.OneHotEncoder,Classifier=sklearn.e nsemble.forest.RandomForestClassifier)(13)Automatically created scikit-learn flow.
sklearn.ensemble.forest.RandomForestClassifier(31)_bootstraptrue
sklearn.ensemble.forest.RandomForestClassifier(31)_class_weightnull
sklearn.ensemble.forest.RandomForestClassifier(31)_criterion"gini"
sklearn.ensemble.forest.RandomForestClassifier(31)_max_depthnull
sklearn.ensemble.forest.RandomForestClassifier(31)_max_features"auto"
sklearn.ensemble.forest.RandomForestClassifier(31)_max_leaf_nodesnull
sklearn.ensemble.forest.RandomForestClassifier(31)_min_impurity_split1e-07
sklearn.ensemble.forest.RandomForestClassifier(31)_min_samples_leaf1
sklearn.ensemble.forest.RandomForestClassifier(31)_min_samples_split2
sklearn.ensemble.forest.RandomForestClassifier(31)_min_weight_fraction_leaf0.0
sklearn.ensemble.forest.RandomForestClassifier(31)_n_estimators10
sklearn.ensemble.forest.RandomForestClassifier(31)_n_jobs1
sklearn.ensemble.forest.RandomForestClassifier(31)_oob_scorefalse
sklearn.ensemble.forest.RandomForestClassifier(31)_random_state25194
sklearn.ensemble.forest.RandomForestClassifier(31)_verbose0
sklearn.ensemble.forest.RandomForestClassifier(31)_warm_startfalse
sklearn.preprocessing.data.OneHotEncoder(18)_categorical_features"all"
sklearn.preprocessing.data.OneHotEncoder(18)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing.data.OneHotEncoder(18)_handle_unknown"ignore"
sklearn.preprocessing.data.OneHotEncoder(18)_n_values"auto"
sklearn.preprocessing.data.OneHotEncoder(18)_sparsefalse
sklearn.preprocessing.imputation.Imputer(17)_axis0
sklearn.preprocessing.imputation.Imputer(17)_copytrue
sklearn.preprocessing.imputation.Imputer(17)_missing_values"NaN"
sklearn.preprocessing.imputation.Imputer(17)_strategy"median"
sklearn.preprocessing.imputation.Imputer(17)_verbose0

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
0.973 ± 0.0307
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9265 ± 0.0499
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.89 ± 0.0738
Cross-validation details (10-fold Crossvalidation)
KB relative information score
130.498 ± 0.797
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0706 ± 0.0252
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4444
Cross-validation details (10-fold Crossvalidation)
Number of instances
150
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9293 ± 0.0461
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9267 ± 0.0492
Cross-validation details (10-fold Crossvalidation)
Prior entropy
1.585
Cross-validation details (10-fold Crossvalidation)
Recall
0.9267 ± 0.0492
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.1589 ± 0.0568
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4714
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.2 ± 0.0714
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.4242 ± 0.1515
Cross-validation details (10-fold Crossvalidation)