DEVELOPMENT... OpenML
Run
123166

Run 123166

Task 3812 (Supervised Classification) arsenic-female-bladder Uploaded 17-12-2014 by Felicia West
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Flow

weka.AdaBoostM1_LWL_DecisionStump(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_LWL_DecisionStump(2)_I80
weka.AdaBoostM1_LWL_DecisionStump(2)_P100
weka.AdaBoostM1_LWL_DecisionStump(2)_S1
weka.AdaBoostM1_LWL_DecisionStump(2)_Wweka.classifiers.lazy.LWL
weka.LWL_DecisionStump(2)_Atrue
weka.LWL_DecisionStump(2)_K-1
weka.LWL_DecisionStump(2)_U0
weka.LWL_DecisionStump(2)_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.

21 Evaluation measures

Area under ROC curve
0.7548
Per class
Build CPU time
43.8361
Build memory
30988768.3578
F measure
0.8318
Per class
Kappa
0.2998
KB relative information score
76.2774
Mean absolute error
0.1665
Mean prior absolute error
0.2462
Number of instances
559
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8285
Per class
Predictive accuracy
0.8354
Prior entropy
0.5956
Recall
0.8354
Per class
Relative absolute error
0.6762
Root mean prior squared error
0.3502
Root mean squared error
0.3939
Root relative squared error
1.1249
SciMark benchmark
899.4388