Run
9184830

Run 9184830

Task 59 (Supervised Classification) iris Uploaded 15-04-2018 by Wenjie Huang
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Flow

sklearn.pipeline.Pipeline(Imputer=sklearn.preprocessing.imputation.Imputer, OneHotEncoder=sklearn.preprocessing.data.OneHotEncoder,Classifier=sklearn.e nsemble.forest.RandomForestClassifier)(12)Automatically created scikit-learn flow.
sklearn.preprocessing.data.OneHotEncoder(17)_categorical_features"all"
sklearn.preprocessing.data.OneHotEncoder(17)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing.data.OneHotEncoder(17)_handle_unknown"ignore"
sklearn.preprocessing.data.OneHotEncoder(17)_n_values"auto"
sklearn.preprocessing.data.OneHotEncoder(17)_sparsefalse
sklearn.pipeline.Pipeline(Imputer=sklearn.preprocessing.imputation.Imputer,OneHotEncoder=sklearn.preprocessing.data.OneHotEncoder,Classifier=sklearn.ensemble.forest.RandomForestClassifier)(12)_memorynull
sklearn.preprocessing.imputation.Imputer(15)_axis0
sklearn.preprocessing.imputation.Imputer(15)_copytrue
sklearn.preprocessing.imputation.Imputer(15)_missing_values"NaN"
sklearn.preprocessing.imputation.Imputer(15)_strategy"median"
sklearn.preprocessing.imputation.Imputer(15)_verbose0
sklearn.ensemble.forest.RandomForestClassifier(32)_bootstraptrue
sklearn.ensemble.forest.RandomForestClassifier(32)_class_weightnull
sklearn.ensemble.forest.RandomForestClassifier(32)_criterion"gini"
sklearn.ensemble.forest.RandomForestClassifier(32)_max_depthnull
sklearn.ensemble.forest.RandomForestClassifier(32)_max_features"auto"
sklearn.ensemble.forest.RandomForestClassifier(32)_max_leaf_nodesnull
sklearn.ensemble.forest.RandomForestClassifier(32)_min_impurity_decrease0.0
sklearn.ensemble.forest.RandomForestClassifier(32)_min_impurity_splitnull
sklearn.ensemble.forest.RandomForestClassifier(32)_min_samples_leaf1
sklearn.ensemble.forest.RandomForestClassifier(32)_min_samples_split2
sklearn.ensemble.forest.RandomForestClassifier(32)_min_weight_fraction_leaf0.0
sklearn.ensemble.forest.RandomForestClassifier(32)_n_estimators10
sklearn.ensemble.forest.RandomForestClassifier(32)_n_jobs1
sklearn.ensemble.forest.RandomForestClassifier(32)_oob_scorefalse
sklearn.ensemble.forest.RandomForestClassifier(32)_random_state39598
sklearn.ensemble.forest.RandomForestClassifier(32)_verbose0
sklearn.ensemble.forest.RandomForestClassifier(32)_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
0.9738 ± 0.0316
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9266 ± 0.0667
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.89 ± 0.0994
Cross-validation details (10-fold Crossvalidation)
KB relative information score
131.5628 ± 0.9522
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0658 ± 0.0296
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
0.9276 ± 0.0658
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9267 ± 0.0663
Cross-validation details (10-fold Crossvalidation)
Prior entropy
1.585
Cross-validation details (10-fold Crossvalidation)
Recall
0.9267 ± 0.0663
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.1481 ± 0.0666
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4714
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1961 ± 0.0775
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.4159 ± 0.1645
Cross-validation details (10-fold Crossvalidation)