Run
2070716

Run 2070716

Task 145685 (Supervised Classification) creditcard Uploaded 19-04-2017 by Daan Vijselaar
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
Issue #Downvotes for this reason By


Flow

weka.AdaBoostM1_CostSensitiveClassifier_FilteredClassifier_SMO_PolyKernel(1 )Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
weka.SMO_PolyKernel(15)_C1.0
weka.SMO_PolyKernel(15)_N0
weka.SMO_PolyKernel(15)_L0.001
weka.SMO_PolyKernel(15)_P1.0E-12
weka.SMO_PolyKernel(15)_V-1
weka.SMO_PolyKernel(15)_W1
weka.SMO_PolyKernel(15)_Kweka.classifiers.functions.supportVector.PolyKernel
weka.SMO_PolyKernel(15)_calibratortrue
weka.PolyKernel(11)_E1.0
weka.PolyKernel(11)_C250007
weka.FilteredClassifier_SMO_PolyKernel(1)_Fweka.filters.unsupervised.instance.RemovePercentage -P 90.0
weka.FilteredClassifier_SMO_PolyKernel(1)_Wweka.classifiers.functions.SMO
weka.CostSensitiveClassifier_FilteredClassifier_SMO_PolyKernel(1)_cost-matrix[0.0 1.0; 500.0 0.0]
weka.CostSensitiveClassifier_FilteredClassifier_SMO_PolyKernel(1)_S1
weka.CostSensitiveClassifier_FilteredClassifier_SMO_PolyKernel(1)_Wweka.classifiers.meta.FilteredClassifier
weka.AdaBoostM1_CostSensitiveClassifier_FilteredClassifier_SMO_PolyKernel(1)_P100
weka.AdaBoostM1_CostSensitiveClassifier_FilteredClassifier_SMO_PolyKernel(1)_S1
weka.AdaBoostM1_CostSensitiveClassifier_FilteredClassifier_SMO_PolyKernel(1)_I10
weka.AdaBoostM1_CostSensitiveClassifier_FilteredClassifier_SMO_PolyKernel(1)_Wweka.classifiers.meta.CostSensitiveClassifier

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
0.938
Per class
Cross-validation details (10-fold Crossvalidation)
Average cost
0.1094
Cross-validation details (10-fold Crossvalidation)
F measure
0.9902
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.1546
Cross-validation details (10-fold Crossvalidation)
KB relative information score
-2065358.1454
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0165
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.0035
Cross-validation details (10-fold Crossvalidation)
Number of instances
284807
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9982
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9835
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.0184
Cross-validation details (10-fold Crossvalidation)
Recall
0.9835
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
4.7849
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.0415
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1285
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
3.0951
Cross-validation details (10-fold Crossvalidation)
Total cost
31152
Cross-validation details (10-fold Crossvalidation)