Run
63897

Run 63897

Task 57 (Supervised Classification) ionosphere Uploaded 17-11-2014 by Joaquin Vanschoren
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
Issue #Downvotes for this reason By


Flow

weka.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
0.8952
Per class
Cross-validation details (10-fold Crossvalidation)
Build CPU time
1.8739
Cross-validation details (10-fold Crossvalidation)
Build memory
1565620685.6752
Cross-validation details (10-fold Crossvalidation)
F measure
0.886
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.7485
Cross-validation details (10-fold Crossvalidation)
KB relative information score
260.3099
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.1149
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4604
Cross-validation details (10-fold Crossvalidation)
Number of instances
351
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
0.892
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8889
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9425
Cross-validation details (10-fold Crossvalidation)
Recall
0.8889
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.2496
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4797
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.3224
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.6721
Cross-validation details (10-fold Crossvalidation)
SciMark benchmark
943.0515