Run
6570

Run 6570

Task 59 (Supervised Classification) iris Uploaded 15-05-2014 by Joaquin Vanschoren
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
Issue #Downvotes for this reason By


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
0.997
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9666
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.95
Cross-validation details (10-fold Crossvalidation)
KB relative information score
140.5983
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0344
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4444
Cross-validation details (10-fold Crossvalidation)
Number of instances
150
Per class
Cross-validation details (10-fold Crossvalidation)
OS information
[Oracle Corporation, 1.7.0_04, x86_64, Mac OS X, 10.9.2]
Precision
0.9678
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9667
Cross-validation details (10-fold Crossvalidation)
Prior entropy
1.585
Cross-validation details (10-fold Crossvalidation)
Recall
0.9667
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.0775
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4714
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.128
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.2714
Cross-validation details (10-fold Crossvalidation)
SciMark benchmark
1363.8301[1008.2315726991381235.2275201472376629.02273766965971195.36716439511252751.301407544408]