Run
10154801

Run 10154801

Task 9 (Supervised Classification) autos Uploaded 13-02-2019 by Hugo Spee
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  • auto-jupyter-notebook openml-python Sklearn_0.20.1.
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Flow

sklearn.pipeline.Pipeline(imputer=sklearn.impute.SimpleImputer,estimator=sc ripts.machineLearningAlgorithms.WithoutOutliersClassifier(classifier=sklear n.neighbors.classification.KNeighborsClassifier,outlierCLF=sklearn.ensemble .iforest.IsolationForest))(1)Automatically created scikit-learn flow.
sklearn.neighbors.classification.KNeighborsClassifier(32)_algorithm"auto"
sklearn.neighbors.classification.KNeighborsClassifier(32)_leaf_size30
sklearn.neighbors.classification.KNeighborsClassifier(32)_metric"minkowski"
sklearn.neighbors.classification.KNeighborsClassifier(32)_metric_paramsnull
sklearn.neighbors.classification.KNeighborsClassifier(32)_n_jobsnull
sklearn.neighbors.classification.KNeighborsClassifier(32)_n_neighbors5
sklearn.neighbors.classification.KNeighborsClassifier(32)_p2
sklearn.neighbors.classification.KNeighborsClassifier(32)_weights"uniform"
sklearn.impute.SimpleImputer(5)_copytrue
sklearn.impute.SimpleImputer(5)_fill_valuenull
sklearn.impute.SimpleImputer(5)_missing_valuesNaN
sklearn.impute.SimpleImputer(5)_strategy"mean"
sklearn.impute.SimpleImputer(5)_verbose0
sklearn.ensemble.iforest.IsolationForest(1)_behaviour"new"
sklearn.ensemble.iforest.IsolationForest(1)_bootstrapfalse
sklearn.ensemble.iforest.IsolationForest(1)_contamination"auto"
sklearn.ensemble.iforest.IsolationForest(1)_max_features1.0
sklearn.ensemble.iforest.IsolationForest(1)_max_samples"auto"
sklearn.ensemble.iforest.IsolationForest(1)_n_estimators100
sklearn.ensemble.iforest.IsolationForest(1)_n_jobsnull
sklearn.ensemble.iforest.IsolationForest(1)_random_state6550
sklearn.ensemble.iforest.IsolationForest(1)_verbose0
sklearn.pipeline.Pipeline(imputer=sklearn.impute.SimpleImputer,estimator=scripts.machineLearningAlgorithms.WithoutOutliersClassifier(classifier=sklearn.neighbors.classification.KNeighborsClassifier,outlierCLF=sklearn.ensemble.iforest.IsolationForest))(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
0.5838 ± 0.0908
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.3575 ± 0.1395
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.1661 ± 0.1744
Cross-validation details (10-fold Crossvalidation)
KB relative information score
46.1845 ± 3.0637
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.1784 ± 0.0417
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.2209 ± 0.0011
Cross-validation details (10-fold Crossvalidation)
Number of instances
205
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.3613 ± 0.1837
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.3756 ± 0.146
Cross-validation details (10-fold Crossvalidation)
Prior entropy
2.3268
Cross-validation details (10-fold Crossvalidation)
Recall
0.3756 ± 0.146
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.8075 ± 0.1878
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3318 ± 0.0017
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.4224 ± 0.0487
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.2731 ± 0.1452
Cross-validation details (10-fold Crossvalidation)