Run
120836

Run 120836

Task 3550 (Supervised Classification) analcatdata_asbestos Uploaded 11-12-2014 by Joaquin Vanschoren
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
Issue #Downvotes for this reason By


Flow

weka.AdaBoostM1_LMT(2)Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
weka.AdaBoostM1_LMT(2)_I40
weka.AdaBoostM1_LMT(2)_P100
weka.AdaBoostM1_LMT(2)_S1
weka.AdaBoostM1_LMT(2)_Wweka.classifiers.trees.LMT
weka.LMT(2)_I-1
weka.LMT(2)_M15
weka.LMT(2)_W0.0

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.

21 Evaluation measures

Area under ROC curve
0.7897
Per class
Cross-validation details (10-fold Crossvalidation)
Build CPU time
1.1844
Cross-validation details (10-fold Crossvalidation)
Build memory
120230574.1687
Cross-validation details (10-fold Crossvalidation)
F measure
0.7443
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.4811
Cross-validation details (10-fold Crossvalidation)
KB relative information score
41.0833
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.2501
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4943
Cross-validation details (10-fold Crossvalidation)
Number of instances
83
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
0.7473
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.747
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9919
Cross-validation details (10-fold Crossvalidation)
Recall
0.747
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.5061
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4971
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.457
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9195
Cross-validation details (10-fold Crossvalidation)
SciMark benchmark
929.7124