Run
63860

Run 63860

Task 3594 (Supervised Classification) analcatdata_supreme Uploaded 17-11-2014 by Joaquin Vanschoren
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Flow

weka.MultiBoostAB_SPegasos(2)Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
weka.SPegasos(2)_E500
weka.SPegasos(2)_F0
weka.SPegasos(2)_L1.0E-4
weka.MultiBoostAB_SPegasos(2)_C3
weka.MultiBoostAB_SPegasos(2)_P100
weka.MultiBoostAB_SPegasos(2)_S1
weka.MultiBoostAB_SPegasos(2)_I80
weka.MultiBoostAB_SPegasos(2)_Wweka.classifiers.functions.SPegasos

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
0.9974
Per class
Cross-validation details (10-fold Crossvalidation)
Build CPU time
2.4758
Cross-validation details (10-fold Crossvalidation)
Build memory
962132624.8134
Cross-validation details (10-fold Crossvalidation)
F measure
0.9894
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.9708
Cross-validation details (10-fold Crossvalidation)
KB relative information score
3851.5643
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0187
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.3645
Cross-validation details (10-fold Crossvalidation)
Number of instances
4052
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
0.9894
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9894
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.7946
Cross-validation details (10-fold Crossvalidation)
Recall
0.9894
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.0513
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4269
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1015
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.2377
Cross-validation details (10-fold Crossvalidation)
SciMark benchmark
943.0515