Run
66752

Run 66752

Task 3732 (Supervised Classification) fri_c4_100_25 Uploaded 30-11-2014 by Joaquin Vanschoren
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
Issue #Downvotes for this reason By


Flow

weka.RealAdaBoost_NaiveBayes(1)J. Friedman, T. Hastie, R. Tibshirani (2000). Additive Logistic Regression: a Statistical View of Boosting. Annals of Statistics. 95(2):337-407.
weka.RealAdaBoost_NaiveBayes(1)_P100
weka.RealAdaBoost_NaiveBayes(1)_H1.0
weka.RealAdaBoost_NaiveBayes(1)_S1
weka.RealAdaBoost_NaiveBayes(1)_I10
weka.RealAdaBoost_NaiveBayes(1)_Wweka.classifiers.bayes.NaiveBayes

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
0.7548
Per class
Cross-validation details (10-fold Crossvalidation)
Build CPU time
0.0068
Cross-validation details (10-fold Crossvalidation)
Build memory
58462526.4
Cross-validation details (10-fold Crossvalidation)
F measure
0.6804
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.3579
Cross-validation details (10-fold Crossvalidation)
KB relative information score
32.4161
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.3406
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4969
Cross-validation details (10-fold Crossvalidation)
Number of instances
100
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
0.6813
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.68
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9956
Cross-validation details (10-fold Crossvalidation)
Recall
0.68
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.6855
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4984
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.4775
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.958
Cross-validation details (10-fold Crossvalidation)
SciMark benchmark
940.03