Run
9268

Run 9268

Task 4 (Supervised Classification) labor 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)_M5
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
0.9824
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9298
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.8459
Cross-validation details (10-fold Crossvalidation)
KB relative information score
43.269
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.1125
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.457
Cross-validation details (10-fold Crossvalidation)
Number of instances
57
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
0.9298
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9298
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9393
Cross-validation details (10-fold Crossvalidation)
Recall
0.9298
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.2461
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4773
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.228
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.4778
Cross-validation details (10-fold Crossvalidation)
SciMark benchmark
949.8387[568.89779800413941015.2555353338006488.5085213342302915.94689394904971760.5845701777503]