OpenML
11703

Run 11703

Task 29 (Supervised Classification) credit-approval Uploaded 22-05-2014 by Joaquin Vanschoren
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Flow

weka.LMT(1)Niels Landwehr, Mark Hall, Eibe Frank (2005). Logistic Model Trees. Machine Learning. 95(1-2):161-205. Marc Sumner, Eibe Frank, Mark Hall: Speeding up Logistic Model Tree Induction. In: 9th European Conference on Principles and Practice of Knowledge Discovery in Databases, 675-683, 2005.
weka.LMT(1)_I-1
weka.LMT(1)_M25
weka.LMT(1)_W0.0

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.

19 Evaluation measures

Area under ROC curve
0.904
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.8511
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.6996
Cross-validation details (10-fold Crossvalidation)
KB relative information score
413.5933
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.2086
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.494
Cross-validation details (10-fold Crossvalidation)
Number of instances
690
Per class
Cross-validation details (10-fold Crossvalidation)
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8527
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8507
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9913
Cross-validation details (10-fold Crossvalidation)
Recall
0.8507
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.4223
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.497
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.3386
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.6813
Cross-validation details (10-fold Crossvalidation)
SciMark benchmark
948.6816[565.39404163109531015.7906865781697483.88543266528814911.48812543402991766.8499488170112]