Run
110607

Run 110607

Task 3810 (Supervised Classification) arsenic-male-bladder Uploaded 09-12-2014 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_IBk(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_IBk(2)_I160
weka.AdaBoostM1_IBk(2)_P100
weka.AdaBoostM1_IBk(2)_S1
weka.AdaBoostM1_IBk(2)_Wweka.classifiers.lazy.IBk
weka.IBk(2)_Atrue
weka.IBk(2)_K1
weka.IBk(2)_W0

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
0.8007
Per class
Cross-validation details (10-fold Crossvalidation)
Build CPU time
0.0225
Cross-validation details (10-fold Crossvalidation)
Build memory
604441129.7317
Cross-validation details (10-fold Crossvalidation)
F measure
0.9663
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.5945
Cross-validation details (10-fold Crossvalidation)
KB relative information score
208.8243
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0358
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
0.9667
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.966
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.2628
Cross-validation details (10-fold Crossvalidation)
Recall
0.966
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.4283
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.2027
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.184
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9077
Cross-validation details (10-fold Crossvalidation)
SciMark benchmark
873.8637