Run
8886395

Run 8886395

Task 167132 (Supervised Classification) Speech Uploaded 16-03-2018 by Yuntao Li
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Flow

imblearn.pipeline.Pipeline(SMOTE=imblearn.over_sampling.smote.SMOTE,Scaler= sklearn.preprocessing.data.MinMaxScaler,Classifier=sklearn.ensemble.forest. RandomForestClassifier)(1)Automatically created scikit-learn flow.
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_features1
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_estimators64
sklearn.ensemble.forest.RandomForestClassifier(32)_n_jobs1
sklearn.ensemble.forest.RandomForestClassifier(32)_oob_scorefalse
sklearn.ensemble.forest.RandomForestClassifier(32)_random_state337
sklearn.ensemble.forest.RandomForestClassifier(32)_verbose0
sklearn.ensemble.forest.RandomForestClassifier(32)_warm_startfalse
sklearn.preprocessing.data.MinMaxScaler(3)_copytrue
sklearn.preprocessing.data.MinMaxScaler(3)_feature_range[0, 1]
imblearn.over_sampling.smote.SMOTE(1)_knull
imblearn.over_sampling.smote.SMOTE(1)_k_neighbors5
imblearn.over_sampling.smote.SMOTE(1)_kind"regular"
imblearn.over_sampling.smote.SMOTE(1)_mnull
imblearn.over_sampling.smote.SMOTE(1)_m_neighbors10
imblearn.over_sampling.smote.SMOTE(1)_n_jobs1
imblearn.over_sampling.smote.SMOTE(1)_out_step0.5
imblearn.over_sampling.smote.SMOTE(1)_random_state12
imblearn.over_sampling.smote.SMOTE(1)_ratio1.0
imblearn.over_sampling.smote.SMOTE(1)_svm_estimatornull
imblearn.pipeline.Pipeline(SMOTE=imblearn.over_sampling.smote.SMOTE,Scaler=sklearn.preprocessing.data.MinMaxScaler,Classifier=sklearn.ensemble.forest.RandomForestClassifier)(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

Area under ROC curve
0.6934 ± 0.1135
Per class
Cross-validation details (10-fold Crossvalidation)
KB relative information score
-67976.484 ± 184.2873
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.1097 ± 0.0038
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.0328 ± 0.0008
Cross-validation details (10-fold Crossvalidation)
Number of instances
3686
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9835 ± 0.0009
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.1231
Cross-validation details (10-fold Crossvalidation)
Recall
0.9835 ± 0.0009
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
3.3448 ± 0.1307
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.1276 ± 0.0031
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1533 ± 0.0042
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.2016 ± 0.0296
Cross-validation details (10-fold Crossvalidation)