DEVELOPMENT... OpenML
Run
54069

Run 54069

Task 1702 (Learning Curve) kr-vs-kp Uploaded 08-11-2014 by Jason
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  • curves study_2 study_37 weka weka_3.7.12-SNAPSHOT
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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
0.9986 ± 0.0023
Per class
Build CPU time
1.0956
Build memory
2189194100.8
F measure
0.9944 ± 0.0051
Per class
Kappa
0.9887 ± 0.0101
KB relative information score
0.9883 ± 0.0093
Mean absolute error
0.0059 ± 0.0046
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
0.9944 ± 0.005
Per class
Predictive accuracy
0.9944 ± 0.0051
Prior entropy
0.9986 ± 0.0002
Recall
0.9944 ± 0.0051
Per class
Relative absolute error
0.0118 ± 0.0092
Root mean prior squared error
0.4995 ± 0.0001
Root mean squared error
0.0716 ± 0.0397
Root relative squared error
0.1434 ± 0.0794
SciMark benchmark
1615.5755