Run
10154697

Run 10154697

Task 9 (Supervised Classification) autos Uploaded 07-02-2019 by Hugo Spee
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  • auto-jupyter-notebook openml-python Sklearn_0.20.1.
Issue #Downvotes for this reason By


Flow

sklearn.pipeline.Pipeline(imputer=sklearn.impute.SimpleImputer,estimator=sc ripts.machineLearningAlgorithms.WithoutOutliersClassifier(classifier=sklear n.ensemble.forest.RandomForestClassifier,outlierCLF=sklearn.ensemble.ifores t.IsolationForest))(1)Automatically created scikit-learn flow.
sklearn.ensemble.forest.RandomForestClassifier(46)_bootstraptrue
sklearn.ensemble.forest.RandomForestClassifier(46)_class_weightnull
sklearn.ensemble.forest.RandomForestClassifier(46)_criterion"gini"
sklearn.ensemble.forest.RandomForestClassifier(46)_max_depthnull
sklearn.ensemble.forest.RandomForestClassifier(46)_max_featuresnull
sklearn.ensemble.forest.RandomForestClassifier(46)_max_leaf_nodesnull
sklearn.ensemble.forest.RandomForestClassifier(46)_min_impurity_decrease0.0
sklearn.ensemble.forest.RandomForestClassifier(46)_min_impurity_splitnull
sklearn.ensemble.forest.RandomForestClassifier(46)_min_samples_leaf1
sklearn.ensemble.forest.RandomForestClassifier(46)_min_samples_split2
sklearn.ensemble.forest.RandomForestClassifier(46)_min_weight_fraction_leaf0.0
sklearn.ensemble.forest.RandomForestClassifier(46)_n_estimators10
sklearn.ensemble.forest.RandomForestClassifier(46)_n_jobsnull
sklearn.ensemble.forest.RandomForestClassifier(46)_oob_scorefalse
sklearn.ensemble.forest.RandomForestClassifier(46)_random_state52804
sklearn.ensemble.forest.RandomForestClassifier(46)_verbose0
sklearn.ensemble.forest.RandomForestClassifier(46)_warm_startfalse
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"old"
sklearn.ensemble.iforest.IsolationForest(1)_bootstrapfalse
sklearn.ensemble.iforest.IsolationForest(1)_contamination"legacy"
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_state5949
sklearn.ensemble.iforest.IsolationForest(1)_verbose0
sklearn.pipeline.Pipeline(imputer=sklearn.impute.SimpleImputer,estimator=scripts.machineLearningAlgorithms.WithoutOutliersClassifier(classifier=sklearn.ensemble.forest.RandomForestClassifier,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.

15 Evaluation measures

0.8615 ± 0.0621
Per class
Cross-validation details (10-fold Crossvalidation)
0.7252 ± 0.1237
Cross-validation details (10-fold Crossvalidation)
147.0897 ± 2.2406
Cross-validation details (10-fold Crossvalidation)
0.0599 ± 0.026
Cross-validation details (10-fold Crossvalidation)
0.2209 ± 0.0011
Cross-validation details (10-fold Crossvalidation)
205
Per class
Cross-validation details (10-fold Crossvalidation)
0.7902 ± 0.0909
Cross-validation details (10-fold Crossvalidation)
2.3268
Cross-validation details (10-fold Crossvalidation)
0.7902 ± 0.0909
Per class
Cross-validation details (10-fold Crossvalidation)
0.2713 ± 0.1183
Cross-validation details (10-fold Crossvalidation)
0.3318 ± 0.0017
Cross-validation details (10-fold Crossvalidation)
0.2448 ± 0.0592
Cross-validation details (10-fold Crossvalidation)
0.7379 ± 0.18
Cross-validation details (10-fold Crossvalidation)