DEVELOPMENT... OpenML
Run
61606

Run 61606

Task 1710 (Learning Curve) balance-scale Uploaded 16-11-2014 by Jason
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  • curves study_2 study_37 weka weka_3.7.12-SNAPSHOT
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Flow

weka.MultiBoostAB_RandomForest(2)Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
weka.RandomForest(2)_I100
weka.RandomForest(2)_K0
weka.RandomForest(2)_S1
weka.RandomForest(2)_num-slots1
weka.MultiBoostAB_RandomForest(2)_C3
weka.MultiBoostAB_RandomForest(2)_P100
weka.MultiBoostAB_RandomForest(2)_S1
weka.MultiBoostAB_RandomForest(2)_I10
weka.MultiBoostAB_RandomForest(2)_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
0.9389 ± 0.0197
Per class
Build CPU time
0.0449
Build memory
1735034979.5
F measure
0.8204 ± 0.0248
Per class
Kappa
0.6788 ± 0.0559
KB relative information score
0.5757 ± 0.051
Mean absolute error
0.1451 ± 0.0229
Mean prior absolute error
0.3798 ± 0.0012
Number of instances
625
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.825 ± 0.0226
Per class
Predictive accuracy
0.816 ± 0.035
Prior entropy
1.3181 ± 0.0124
Recall
0.816 ± 0.035
Per class
Relative absolute error
0.382 ± 0.0603
Root mean prior squared error
0.4356 ± 0.0014
Root mean squared error
0.2913 ± 0.0297
Root relative squared error
0.6688 ± 0.0683
SciMark benchmark
1559.5381