DEVELOPMENT... OpenML
Run
47241

Run 47241

Task 1710 (Learning Curve) balance-scale Uploaded 05-11-2014 by Jason
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  • curves study_2 study_37 weka weka_3.7.12-SNAPSHOT
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Flow

weka.Bagging_RandomForest(2)Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
weka.Bagging_RandomForest(2)_I10
weka.Bagging_RandomForest(2)_P100
weka.Bagging_RandomForest(2)_S1
weka.Bagging_RandomForest(2)_Wweka.classifiers.trees.RandomForest
weka.Bagging_RandomForest(2)_num-slots1
weka.RandomForest(2)_I100
weka.RandomForest(2)_K0
weka.RandomForest(2)_S1
weka.RandomForest(2)_num-slots1

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
0.95 ± 0.0165
Per class
Build CPU time
0.2658
Build memory
850718030.1
F measure
0.8358 ± 0.0241
Per class
Kappa
0.7193 ± 0.061
KB relative information score
0.5736 ± 0.0447
Mean absolute error
0.1519 ± 0.0194
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
0.8301 ± 0.0196
Per class
Predictive accuracy
0.8416 ± 0.0377
Prior entropy
1.3181 ± 0.0124
Recall
0.8416 ± 0.0377
Per class
Relative absolute error
0.4001 ± 0.0509
Root mean prior squared error
0.4356 ± 0.0014
Root mean squared error
0.273 ± 0.0217
Root relative squared error
0.6267 ± 0.0498
SciMark benchmark
1631.9056