Run
421905

Run 421905

Task 4517 (Supervised Classification) arsenic-female-bladder Uploaded 08-05-2015 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_DecisionStump(3)Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
weka.MultiBoostAB_DecisionStump(3)_C3
weka.MultiBoostAB_DecisionStump(3)_P100
weka.MultiBoostAB_DecisionStump(3)_S1
weka.MultiBoostAB_DecisionStump(3)_I160
weka.MultiBoostAB_DecisionStump(3)_Wweka.classifiers.trees.DecisionStump

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.

22 Evaluation measures

Area under ROC curve
0.8018
Per class
Cross-validation details (10 times 10-fold Crossvalidation)
F measure
0.8216
Per class
Cross-validation details (10 times 10-fold Crossvalidation)
Kappa
0.1539
Cross-validation details (10 times 10-fold Crossvalidation)
KB relative information score
1850.7224
Cross-validation details (10 times 10-fold Crossvalidation)
Mean absolute error
0.1313
Cross-validation details (10 times 10-fold Crossvalidation)
Mean prior absolute error
0.2462
Cross-validation details (10 times 10-fold Crossvalidation)
Number of instances
5590
Per class
Cross-validation details (10 times 10-fold Crossvalidation)
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8731
Per class
Cross-validation details (10 times 10-fold Crossvalidation)
Predictive accuracy
0.8694
Cross-validation details (10 times 10-fold Crossvalidation)
Prior entropy
0.5956
Cross-validation details (10 times 10-fold Crossvalidation)
Recall
0.8694
Per class
Cross-validation details (10 times 10-fold Crossvalidation)
Relative absolute error
0.5335
Cross-validation details (10 times 10-fold Crossvalidation)
Root mean prior squared error
0.3502
Cross-validation details (10 times 10-fold Crossvalidation)
Root mean squared error
0.3565
Cross-validation details (10 times 10-fold Crossvalidation)
Root relative squared error
1.0179
Cross-validation details (10 times 10-fold Crossvalidation)
SciMark benchmark
938.3115
UserCPU time millis
120
Cross-validation details (10 times 10-fold Crossvalidation)
UserCPU time millis testing
10
Cross-validation details (10 times 10-fold Crossvalidation)
UserCPU time millis training
110
Cross-validation details (10 times 10-fold Crossvalidation)