Run
54128

Run 54128

Task 1742 (Learning Curve) spambase Uploaded 08-11-2014 by Jan van Rijn
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  • curves study_2 study_37 weka weka_3.7.12-SNAPSHOT
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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)_I10
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
0.9571 ± 0.0115
Per class
Build CPU time
755.5311
Build memory
83295507.4286
F measure
0.8911 ± 0.0232
Per class
Kappa
0.7712 ± 0.0495
KB relative information score
0.6993 ± 0.0324
Mean absolute error
0.1509 ± 0.0143
Mean prior absolute error
0.4776 ± 0.0002
Number of instances
4601
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.8912 ± 0.0217
Per class
Predictive accuracy
0.8915 ± 0.0223
Prior entropy
0.9674 ± 0.0006
Recall
0.8915 ± 0.0223
Per class
Relative absolute error
0.3159 ± 0.0301
Root mean prior squared error
0.4886 ± 0.0002
Root mean squared error
0.2795 ± 0.0222
Root relative squared error
0.572 ± 0.0456
SciMark benchmark
1608.8422