DEVELOPMENT... OpenML
Run
54080

Run 54080

Task 1736 (Learning Curve) diabetes 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
0.8223 ± 0.0386
Per class
Build CPU time
0.6215
Build memory
1429949708.6
F measure
0.7577 ± 0.0429
Per class
Kappa
0.4602 ± 0.1004
KB relative information score
0.4452 ± 0.0851
Mean absolute error
0.2429 ± 0.0361
Mean prior absolute error
0.4545 ± 0.0015
Number of instances
768
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.7567 ± 0.0432
Per class
Predictive accuracy
0.7617 ± 0.0382
Prior entropy
0.9331 ± 0.0046
Recall
0.7617 ± 0.0382
Per class
Relative absolute error
0.5345 ± 0.0798
Root mean prior squared error
0.4766 ± 0.0016
Root mean squared error
0.4642 ± 0.0372
Root relative squared error
0.9738 ± 0.0785
SciMark benchmark
1615.5755