DEVELOPMENT... OpenML
Run
47258

Run 47258

Task 1722 (Learning Curve) cmc Uploaded 05-11-2014 by Jason
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  • 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
0.6874 ± 0.0229
Per class
Build CPU time
0.5703
Build memory
887190494.32
F measure
0.5038 ± 0.0329
Per class
Kappa
0.2286 ± 0.0534
KB relative information score
0.2281 ± 0.0221
Mean absolute error
0.3632 ± 0.009
Mean prior absolute error
0.4308 ± 0.0004
Number of instances
1473
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.503 ± 0.032
Per class
Predictive accuracy
0.5064 ± 0.0334
Prior entropy
1.539 ± 0.0029
Recall
0.5064 ± 0.0334
Per class
Relative absolute error
0.843 ± 0.0214
Root mean prior squared error
0.4641 ± 0.0005
Root mean squared error
0.4492 ± 0.0075
Root relative squared error
0.9679 ± 0.0166
SciMark benchmark
1445.6628