DEVELOPMENT... OpenML
Run
123719

Run 123719

Task 3810 (Supervised Classification) arsenic-male-bladder Uploaded 20-12-2014 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)_I40
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
0.7985
Per class
Build CPU time
21.827
Build memory
32247945.1449
F measure
0.9657
Per class
Kappa
0.578
KB relative information score
202.6912
Mean absolute error
0.0342
Mean prior absolute error
0.0837
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
0.9653
Per class
Predictive accuracy
0.966
Prior entropy
0.2628
Recall
0.966
Per class
Relative absolute error
0.4086
Root mean prior squared error
0.2027
Root mean squared error
0.1813
Root relative squared error
0.8944
SciMark benchmark
939.521