DEVELOPMENT... OpenML
Run
54077

Run 54077

Task 1728 (Learning Curve) credit-approval Uploaded 08-11-2014 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.RealAdaBoost_RandomForest(1)J. Friedman, T. Hastie, R. Tibshirani (2000). Additive Logistic Regression: a Statistical View of Boosting. Annals of Statistics. 95(2):337-407.
weka.RandomForest(2)_I100
weka.RandomForest(2)_K0
weka.RandomForest(2)_S1
weka.RandomForest(2)_num-slots1
weka.RealAdaBoost_RandomForest(1)_P100
weka.RealAdaBoost_RandomForest(1)_H1.0
weka.RealAdaBoost_RandomForest(1)_S1
weka.RealAdaBoost_RandomForest(1)_I10
weka.RealAdaBoost_RandomForest(1)_Wweka.classifiers.trees.RandomForest

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
0.9144 ± 0.0443
Per class
Build CPU time
0.475
Build memory
1779627095.1
F measure
0.8504 ± 0.0331
Per class
Kappa
0.6965 ± 0.0677
KB relative information score
0.7015 ± 0.0684
Mean absolute error
0.1466 ± 0.0338
Mean prior absolute error
0.494 ± 0.0008
Number of instances
690
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.8506 ± 0.0331
Per class
Predictive accuracy
0.8507 ± 0.0328
Prior entropy
0.9912 ± 0.0022
Recall
0.8507 ± 0.0328
Per class
Relative absolute error
0.2967 ± 0.0685
Root mean prior squared error
0.497 ± 0.0008
Root mean squared error
0.3673 ± 0.046
Root relative squared error
0.7391 ± 0.0928
SciMark benchmark
1615.5755