Run
8603319

Run 8603319

Task 59 (Supervised Classification) iris Uploaded 01-12-2017 by Continuous Integration
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
Issue #Downvotes for this reason By


Flow

sklearn.pipeline.Pipeline(Imputer=sklearn.preprocessing.imputation.Imputer, OneHotEncoder=sklearn.preprocessing.data.OneHotEncoder,Classifier=sklearn.e nsemble.forest.RandomForestClassifier)(10)Automatically created scikit-learn flow.
sklearn.preprocessing.imputation.Imputer(13)_axis0
sklearn.preprocessing.imputation.Imputer(13)_copytrue
sklearn.preprocessing.imputation.Imputer(13)_missing_values"NaN"
sklearn.preprocessing.imputation.Imputer(13)_strategy"median"
sklearn.preprocessing.imputation.Imputer(13)_verbose0
sklearn.preprocessing.data.OneHotEncoder(14)_categorical_features"all"
sklearn.preprocessing.data.OneHotEncoder(14)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing.data.OneHotEncoder(14)_handle_unknown"ignore"
sklearn.preprocessing.data.OneHotEncoder(14)_n_values"auto"
sklearn.preprocessing.data.OneHotEncoder(14)_sparsefalse
sklearn.ensemble.forest.RandomForestClassifier(29)_bootstraptrue
sklearn.ensemble.forest.RandomForestClassifier(29)_class_weightnull
sklearn.ensemble.forest.RandomForestClassifier(29)_criterion"gini"
sklearn.ensemble.forest.RandomForestClassifier(29)_max_depthnull
sklearn.ensemble.forest.RandomForestClassifier(29)_max_features"auto"
sklearn.ensemble.forest.RandomForestClassifier(29)_max_leaf_nodesnull
sklearn.ensemble.forest.RandomForestClassifier(29)_min_impurity_split1e-07
sklearn.ensemble.forest.RandomForestClassifier(29)_min_samples_leaf1
sklearn.ensemble.forest.RandomForestClassifier(29)_min_samples_split2
sklearn.ensemble.forest.RandomForestClassifier(29)_min_weight_fraction_leaf0.0
sklearn.ensemble.forest.RandomForestClassifier(29)_n_estimators10
sklearn.ensemble.forest.RandomForestClassifier(29)_n_jobs1
sklearn.ensemble.forest.RandomForestClassifier(29)_oob_scorefalse
sklearn.ensemble.forest.RandomForestClassifier(29)_random_state836
sklearn.ensemble.forest.RandomForestClassifier(29)_verbose0
sklearn.ensemble.forest.RandomForestClassifier(29)_warm_startfalse

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
0.9741 ± 0.0277
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9466 ± 0.0619
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.92 ± 0.0919
Cross-validation details (10-fold Crossvalidation)
KB relative information score
132.1921 ± 0.8961
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0651 ± 0.0276
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
0.9485 ± 0.0586
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9467 ± 0.0613
Cross-validation details (10-fold Crossvalidation)
Prior entropy
1.585
Cross-validation details (10-fold Crossvalidation)
Recall
0.9467 ± 0.0613
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.1465 ± 0.0622
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4714
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1896 ± 0.0719
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.4022 ± 0.1526
Cross-validation details (10-fold Crossvalidation)