Run
52237

Run 52237

Task 1702 (Learning Curve) kr-vs-kp Uploaded 07-11-2014 by Jan van Rijn
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.RealAdaBoost_RandomTree(1)J. Friedman, T. Hastie, R. Tibshirani (2000). Additive Logistic Regression: a Statistical View of Boosting. Annals of Statistics. 95(2):337-407.
weka.RandomTree(2)_K0
weka.RandomTree(2)_M1.0
weka.RandomTree(2)_S1
weka.RandomTree(2)_V0.001
weka.RealAdaBoost_RandomTree(1)_P100
weka.RealAdaBoost_RandomTree(1)_H1.0
weka.RealAdaBoost_RandomTree(1)_S1
weka.RealAdaBoost_RandomTree(1)_I10
weka.RealAdaBoost_RandomTree(1)_Wweka.classifiers.trees.RandomTree

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
0.9929 ± 0.0032
Per class
Build CPU time
0.0135
Build memory
300453171.2
F measure
0.9909 ± 0.0034
Per class
Kappa
0.9818 ± 0.0069
KB relative information score
0.9824 ± 0.0059
Mean absolute error
0.0088 ± 0.003
Mean prior absolute error
0.499 ± 0.0001
Number of instances
3196
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.991 ± 0.0033
Per class
Predictive accuracy
0.9909 ± 0.0034
Prior entropy
0.9986 ± 0.0002
Recall
0.9909 ± 0.0034
Per class
Relative absolute error
0.0176 ± 0.0059
Root mean prior squared error
0.4995 ± 0.0001
Root mean squared error
0.0885 ± 0.0179
Root relative squared error
0.1772 ± 0.0359
SciMark benchmark
1653.7854