DEVELOPMENT... OpenML
Run
48640

Run 48640

Task 1702 (Learning Curve) kr-vs-kp 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
0.9984 ± 0.0023
Per class
Build CPU time
0.4528
Build memory
1339831476.5333
F measure
0.9966 ± 0.0048
Per class
Kappa
0.9931 ± 0.0095
KB relative information score
0.9929 ± 0.0097
Mean absolute error
0.0036 ± 0.0048
Mean prior absolute error
0.499 ± 0.0001
Number of instances
3196
Per class
OS information
[Oracle Corporation, 1.7.0_65, amd64, Linux, 3.5.0-54-generic]
Precision
0.9966 ± 0.0047
Per class
Predictive accuracy
0.9966 ± 0.0048
Prior entropy
0.9986 ± 0.0002
Recall
0.9966 ± 0.0048
Per class
Relative absolute error
0.0071 ± 0.0097
Root mean prior squared error
0.4995 ± 0.0001
Root mean squared error
0.0586 ± 0.0421
Root relative squared error
0.1173 ± 0.0843
SciMark benchmark
1932.1045