Run
7947987

Run 7947987

Task 59 (Supervised Classification) iris Uploaded 10-10-2017 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)(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_state17922
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

0.9767 ± 0.0285
Per class
Cross-validation details (10-fold Crossvalidation)
0.9398 ± 0.059
Per class
Cross-validation details (10-fold Crossvalidation)
0.91 ± 0.0876
Cross-validation details (10-fold Crossvalidation)
132.9749 ± 0.9217
Cross-validation details (10-fold Crossvalidation)
0.0614 ± 0.0296
Cross-validation details (10-fold Crossvalidation)
0.4444
Cross-validation details (10-fold Crossvalidation)
150
Per class
Cross-validation details (10-fold Crossvalidation)
0.9428 ± 0.0562
Per class
Cross-validation details (10-fold Crossvalidation)
0.94 ± 0.0584
Cross-validation details (10-fold Crossvalidation)
1.585
Cross-validation details (10-fold Crossvalidation)
0.94 ± 0.0584
Per class
Cross-validation details (10-fold Crossvalidation)
0.1383 ± 0.0665
Cross-validation details (10-fold Crossvalidation)
0.4714
Cross-validation details (10-fold Crossvalidation)
0.19 ± 0.0755
Cross-validation details (10-fold Crossvalidation)
0.4031 ± 0.1601
Cross-validation details (10-fold Crossvalidation)