Run
10154622

Run 10154622

Task 43 (Supervised Classification) spambase Uploaded 06-02-2019 by Sarim Zafar
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Flow

sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,decisi ontreeclassifier=sklearn.tree.tree.DecisionTreeClassifier)(2)Automatically created scikit-learn flow.
sklearn.tree.tree.DecisionTreeClassifier(33)_class_weightnull
sklearn.tree.tree.DecisionTreeClassifier(33)_criterion"gini"
sklearn.tree.tree.DecisionTreeClassifier(33)_max_depthnull
sklearn.tree.tree.DecisionTreeClassifier(33)_max_featuresnull
sklearn.tree.tree.DecisionTreeClassifier(33)_max_leaf_nodesnull
sklearn.tree.tree.DecisionTreeClassifier(33)_min_impurity_decrease0.0
sklearn.tree.tree.DecisionTreeClassifier(33)_min_impurity_splitnull
sklearn.tree.tree.DecisionTreeClassifier(33)_min_samples_leaf1
sklearn.tree.tree.DecisionTreeClassifier(33)_min_samples_split2
sklearn.tree.tree.DecisionTreeClassifier(33)_min_weight_fraction_leaf0.0
sklearn.tree.tree.DecisionTreeClassifier(33)_presortfalse
sklearn.tree.tree.DecisionTreeClassifier(33)_random_state13758
sklearn.tree.tree.DecisionTreeClassifier(33)_splitter"best"
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,decisiontreeclassifier=sklearn.tree.tree.DecisionTreeClassifier)(2)_memorynull
sklearn.impute.SimpleImputer(7)_copytrue
sklearn.impute.SimpleImputer(7)_fill_valuenull
sklearn.impute.SimpleImputer(7)_missing_valuesNaN
sklearn.impute.SimpleImputer(7)_strategy"mean"
sklearn.impute.SimpleImputer(7)_verbose0

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
0.9161 ± 0.0151
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.918 ± 0.0138
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.8287 ± 0.0289
Cross-validation details (10-fold Crossvalidation)
KB relative information score
3789.0928 ± 13.4075
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0826 ± 0.0136
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4776 ± 0.0002
Cross-validation details (10-fold Crossvalidation)
Number of instances
4601
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9184 ± 0.0138
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9178 ± 0.0138
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9674
Cross-validation details (10-fold Crossvalidation)
Recall
0.9178 ± 0.0138
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.1729 ± 0.0286
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4886 ± 0.0002
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.287 ± 0.0246
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.5874 ± 0.0504
Cross-validation details (10-fold Crossvalidation)