DEVELOPMENT... OpenML
Run
48666

Run 48666

Task 1742 (Learning Curve) spambase Uploaded 05-11-2014 by Jason
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
  • curves study_2 study_37 weka weka_3.7.12-SNAPSHOT
Issue #Downvotes for this reason By


Flow

weka.AdaBoostM1_JRip(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_JRip(2)_I10
weka.AdaBoostM1_JRip(2)_P100
weka.AdaBoostM1_JRip(2)_S1
weka.AdaBoostM1_JRip(2)_Wweka.classifiers.rules.JRip
weka.JRip(2)_F3
weka.JRip(2)_N2.0
weka.JRip(2)_O2
weka.JRip(2)_S1

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
0.9795 ± 0.0056
Per class
Build CPU time
1.6084
Build memory
2223902866.1143
F measure
0.9443 ± 0.0111
Per class
Kappa
0.8834 ± 0.0233
KB relative information score
0.8692 ± 0.0219
Mean absolute error
0.063 ± 0.0099
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
0.9443 ± 0.011
Per class
Predictive accuracy
0.9444 ± 0.0111
Prior entropy
0.9674 ± 0.0006
Recall
0.9444 ± 0.0111
Per class
Relative absolute error
0.1319 ± 0.0208
Root mean prior squared error
0.4886 ± 0.0002
Root mean squared error
0.2159 ± 0.0241
Root relative squared error
0.4419 ± 0.0494
SciMark benchmark
1723.761