Run
9204529

Run 9204529

Task 22 (Supervised Classification) mfeat-zernike Uploaded 17-09-2018 by Roel Zinkstok
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Flow

sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer, decisiontreeclassifier=sklearn.tree.tree.DecisionTreeClassifier)(6)Automatically created scikit-learn flow.
sklearn.preprocessing.imputation.Imputer(26)_axis0
sklearn.preprocessing.imputation.Imputer(26)_copytrue
sklearn.preprocessing.imputation.Imputer(26)_missing_values"NaN"
sklearn.preprocessing.imputation.Imputer(26)_strategy"mean"
sklearn.preprocessing.imputation.Imputer(26)_verbose0
sklearn.tree.tree.DecisionTreeClassifier(27)_class_weightnull
sklearn.tree.tree.DecisionTreeClassifier(27)_criterion"gini"
sklearn.tree.tree.DecisionTreeClassifier(27)_max_depthnull
sklearn.tree.tree.DecisionTreeClassifier(27)_max_featuresnull
sklearn.tree.tree.DecisionTreeClassifier(27)_max_leaf_nodesnull
sklearn.tree.tree.DecisionTreeClassifier(27)_min_impurity_decrease0.0
sklearn.tree.tree.DecisionTreeClassifier(27)_min_impurity_splitnull
sklearn.tree.tree.DecisionTreeClassifier(27)_min_samples_leaf1
sklearn.tree.tree.DecisionTreeClassifier(27)_min_samples_split2
sklearn.tree.tree.DecisionTreeClassifier(27)_min_weight_fraction_leaf0.0
sklearn.tree.tree.DecisionTreeClassifier(27)_presortfalse
sklearn.tree.tree.DecisionTreeClassifier(27)_random_state56044
sklearn.tree.tree.DecisionTreeClassifier(27)_splitter"best"
sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,decisiontreeclassifier=sklearn.tree.tree.DecisionTreeClassifier)(6)_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.

17 Evaluation measures

Area under ROC curve
0.8128 ± 0.0119
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.6638 ± 0.0201
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.6256 ± 0.0239
Cross-validation details (10-fold Crossvalidation)
KB relative information score
1295.1595 ± 4.4966
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0674 ± 0.0043
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.18
Cross-validation details (10-fold Crossvalidation)
Number of instances
2000
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.6649 ± 0.0209
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.663 ± 0.0215
Cross-validation details (10-fold Crossvalidation)
Prior entropy
3.3219
Cross-validation details (10-fold Crossvalidation)
Recall
0.663 ± 0.0215
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.3744 ± 0.0239
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.2596 ± 0.0084
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.8654 ± 0.028
Cross-validation details (10-fold Crossvalidation)