Run
498384

Run 498384

Task 10106 (Supervised Classification) CreditCardSubset Uploaded 04-12-2015 by Guido Santegoeds
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
Issue #Downvotes for this reason By


Flow

weka.AttributeSelectedClassifier_CfsSubsetEval_BestFirst_CostSensitiveClass ifier_AdaBoostM1_REPTree(1)Weka implementation of AttributeSelectedClassifier
weka.REPTree(15)_M2
weka.REPTree(15)_V0.001
weka.REPTree(15)_N3
weka.REPTree(15)_S1
weka.REPTree(15)_L-1
weka.REPTree(15)_I0.0
weka.CfsSubsetEval(5)_P1
weka.CfsSubsetEval(5)_E1
weka.BestFirst(4)_D1
weka.BestFirst(4)_N5
weka.AttributeSelectedClassifier_CfsSubsetEval_BestFirst_CostSensitiveClassifier_AdaBoostM1_REPTree(1)_Eweka.attributeSelection.CfsSubsetEval
weka.AttributeSelectedClassifier_CfsSubsetEval_BestFirst_CostSensitiveClassifier_AdaBoostM1_REPTree(1)_Sweka.attributeSelection.BestFirst
weka.AttributeSelectedClassifier_CfsSubsetEval_BestFirst_CostSensitiveClassifier_AdaBoostM1_REPTree(1)_Wweka.classifiers.meta.CostSensitiveClassifier
weka.AttributeSelectedClassifier_CfsSubsetEval_BestFirst_CostSensitiveClassifier_AdaBoostM1_REPTree(1)_num-decimal-places4
weka.CostSensitiveClassifier_AdaBoostM1_REPTree(5)_Mtrue
weka.CostSensitiveClassifier_AdaBoostM1_REPTree(5)_cost-matrix[0.0 1.0; 500.0 0.0]
weka.CostSensitiveClassifier_AdaBoostM1_REPTree(5)_S1
weka.CostSensitiveClassifier_AdaBoostM1_REPTree(5)_Wweka.classifiers.meta.AdaBoostM1
weka.CostSensitiveClassifier_AdaBoostM1_REPTree(5)_num-decimal-places4
weka.AdaBoostM1_REPTree(7)_P100
weka.AdaBoostM1_REPTree(7)_S1
weka.AdaBoostM1_REPTree(7)_I20
weka.AdaBoostM1_REPTree(7)_Wweka.classifiers.trees.REPTree

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

model
Model readable

A human-readable description of the model that was built.

model
Model serialized

A serialized description of the model that can be read by the tool that generated it.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

17 Evaluation measures

Area under ROC curve
0.8474
Per class
Cross-validation details (10-fold Crossvalidation)
Average cost
0.2466
Cross-validation details (10-fold Crossvalidation)
F measure
0.9987
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.6268
Cross-validation details (10-fold Crossvalidation)
KB relative information score
3976.6761
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0013
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.0033
Cross-validation details (10-fold Crossvalidation)
Number of instances
14240
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9988
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9987
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.018
Cross-validation details (10-fold Crossvalidation)
Recall
0.9987
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.405
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.0402
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.0365
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9096
Cross-validation details (10-fold Crossvalidation)
Total cost
3512
Cross-validation details (10-fold Crossvalidation)