Run
41108

Run 41108

Task 3810 (Supervised Classification) arsenic-male-bladder Uploaded 29-10-2014 by Joaquin Vanschoren
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
Issue #Downvotes for this reason By


Flow

weka.MultiBoostAB_ADTree(2)Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
weka.ADTree(2)_B10
weka.ADTree(2)_E-3
weka.ADTree(2)_S1
weka.MultiBoostAB_ADTree(2)_C3
weka.MultiBoostAB_ADTree(2)_P100
weka.MultiBoostAB_ADTree(2)_S1
weka.MultiBoostAB_ADTree(2)_I80
weka.MultiBoostAB_ADTree(2)_Wweka.classifiers.trees.ADTree

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
0.7878
Per class
Cross-validation details (10-fold Crossvalidation)
Build CPU time
0.8206
Cross-validation details (10-fold Crossvalidation)
Build memory
971870099.3775
Cross-validation details (10-fold Crossvalidation)
F measure
0.9742
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.6553
Cross-validation details (10-fold Crossvalidation)
KB relative information score
311.2845
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0236
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.0837
Cross-validation details (10-fold Crossvalidation)
Number of instances
559
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
0.9749
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9767
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.2628
Cross-validation details (10-fold Crossvalidation)
Recall
0.9767
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.2815
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.2027
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1521
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.7503
Cross-validation details (10-fold Crossvalidation)
SciMark benchmark
941.4198