DEVELOPMENT... OpenML
Run
53768

Run 53768

Task 1735 (Learning Curve) segment 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.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
0.9994 ± 0.0006
Per class
Build CPU time
0.1661
Build memory
2850266600.8
F measure
0.9827 ± 0.0064
Per class
Kappa
0.9798 ± 0.0075
KB relative information score
0.9613 ± 0.0089
Mean absolute error
0.0163 ± 0.0032
Mean prior absolute error
0.2449
Number of instances
2310
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.9827 ± 0.0062
Per class
Predictive accuracy
0.9827 ± 0.0065
Prior entropy
2.8074
Recall
0.9827 ± 0.0065
Per class
Relative absolute error
0.0667 ± 0.0132
Root mean prior squared error
0.3499
Root mean squared error
0.0699 ± 0.0113
Root relative squared error
0.1999 ± 0.0324
SciMark benchmark
1624.8488