DEVELOPMENT... OpenML
Run
51826

Run 51826

Task 1752 (Learning Curve) vehicle Uploaded 07-11-2014 by Jason
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  • curves study_2 study_37 weka weka_3.7.12-SNAPSHOT
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Flow

weka.MultiBoostAB_REPTree(2)Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
weka.REPTree(5)_I0.0
weka.REPTree(5)_L-1
weka.REPTree(5)_M2
weka.REPTree(5)_N3
weka.REPTree(5)_S1
weka.REPTree(5)_V0.001
weka.MultiBoostAB_REPTree(2)_C3
weka.MultiBoostAB_REPTree(2)_P100
weka.MultiBoostAB_REPTree(2)_S1
weka.MultiBoostAB_REPTree(2)_I10
weka.MultiBoostAB_REPTree(2)_Wweka.classifiers.trees.REPTree

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
0.9168 ± 0.0218
Per class
Build CPU time
0.0402
Build memory
460884624.1778
F measure
0.7247 ± 0.0594
Per class
Kappa
0.6439 ± 0.0728
KB relative information score
0.6771 ± 0.0586
Mean absolute error
0.1373 ± 0.0236
Mean prior absolute error
0.3748 ± 0
Number of instances
846
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.7195 ± 0.061
Per class
Predictive accuracy
0.7329 ± 0.0549
Prior entropy
1.9991 ± 0.0005
Recall
0.7329 ± 0.0549
Per class
Relative absolute error
0.3663 ± 0.0629
Root mean prior squared error
0.4329 ± 0
Root mean squared error
0.3344 ± 0.0364
Root relative squared error
0.7724 ± 0.0842
SciMark benchmark
1638.2006