Run
7946965

Run 7946965

Task 59 (Supervised Classification) iris Uploaded 09-10-2017 by Andreas Mueller
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Flow

sklearn.pipeline.Pipeline(Imputer=sklearn.preprocessing.imputation.Imputer, OneHotEncoder=sklearn.preprocessing.data.OneHotEncoder,Classifier=sklearn.e nsemble.forest.RandomForestClassifier)(9)Automatically created scikit-learn flow.
sklearn.ensemble.forest.RandomForestClassifier(28)_bootstraptrue
sklearn.ensemble.forest.RandomForestClassifier(28)_class_weightnull
sklearn.ensemble.forest.RandomForestClassifier(28)_criterion"gini"
sklearn.ensemble.forest.RandomForestClassifier(28)_max_depthnull
sklearn.ensemble.forest.RandomForestClassifier(28)_max_features"auto"
sklearn.ensemble.forest.RandomForestClassifier(28)_max_leaf_nodesnull
sklearn.ensemble.forest.RandomForestClassifier(28)_min_impurity_split1e-07
sklearn.ensemble.forest.RandomForestClassifier(28)_min_samples_leaf1
sklearn.ensemble.forest.RandomForestClassifier(28)_min_samples_split2
sklearn.ensemble.forest.RandomForestClassifier(28)_min_weight_fraction_leaf0.0
sklearn.ensemble.forest.RandomForestClassifier(28)_n_estimators10
sklearn.ensemble.forest.RandomForestClassifier(28)_n_jobs1
sklearn.ensemble.forest.RandomForestClassifier(28)_oob_scorefalse
sklearn.ensemble.forest.RandomForestClassifier(28)_random_state61667
sklearn.ensemble.forest.RandomForestClassifier(28)_verbose0
sklearn.ensemble.forest.RandomForestClassifier(28)_warm_startfalse
sklearn.preprocessing.imputation.Imputer(12)_axis0
sklearn.preprocessing.imputation.Imputer(12)_copytrue
sklearn.preprocessing.imputation.Imputer(12)_missing_values"NaN"
sklearn.preprocessing.imputation.Imputer(12)_strategy"median"
sklearn.preprocessing.imputation.Imputer(12)_verbose0
sklearn.preprocessing.data.OneHotEncoder(13)_categorical_features"all"
sklearn.preprocessing.data.OneHotEncoder(13)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing.data.OneHotEncoder(13)_handle_unknown"ignore"
sklearn.preprocessing.data.OneHotEncoder(13)_n_values"auto"
sklearn.preprocessing.data.OneHotEncoder(13)_sparsefalse

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
0.978 ± 0.0248
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9399 ± 0.0492
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.91 ± 0.0738
Cross-validation details (10-fold Crossvalidation)
KB relative information score
130.8931 ± 0.8118
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0691 ± 0.0265
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
0.941 ± 0.0487
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.94 ± 0.0492
Cross-validation details (10-fold Crossvalidation)
Prior entropy
1.585
Cross-validation details (10-fold Crossvalidation)
Recall
0.94 ± 0.0492
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.1554 ± 0.0596
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4714
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1954 ± 0.0642
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.4145 ± 0.1361
Cross-validation details (10-fold Crossvalidation)