DEVELOPMENT... OpenML
Run
51818

Run 51818

Task 1721 (Learning Curve) mfeat-zernike 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
0.9608 ± 0.0096
Per class
Build CPU time
0.476
Build memory
570560316.7273
F measure
0.7545 ± 0.0279
Per class
Kappa
0.7294 ± 0.0303
KB relative information score
0.759 ± 0.0306
Mean absolute error
0.0516 ± 0.0054
Mean prior absolute error
0.18
Number of instances
2000
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.7559 ± 0.0299
Per class
Predictive accuracy
0.7565 ± 0.0273
Prior entropy
3.3219
Recall
0.7565 ± 0.0273
Per class
Relative absolute error
0.2867 ± 0.0301
Root mean prior squared error
0.3
Root mean squared error
0.1958 ± 0.0131
Root relative squared error
0.6528 ± 0.0436
SciMark benchmark
1638.2006