Run
51810

Run 51810

Task 1715 (Learning Curve) mfeat-karhunen Uploaded 07-11-2014 by Jan van Rijn
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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
0.9905 ± 0.004
Per class
Build CPU time
0.5905
Build memory
320278711.2727
F measure
0.8968 ± 0.0195
Per class
Kappa
0.8856 ± 0.0208
KB relative information score
0.8977 ± 0.0182
Mean absolute error
0.0221 ± 0.0038
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
0.8972 ± 0.021
Per class
Predictive accuracy
0.897 ± 0.0187
Prior entropy
3.3219
Recall
0.897 ± 0.0187
Per class
Relative absolute error
0.1228 ± 0.0212
Root mean prior squared error
0.3
Root mean squared error
0.1278 ± 0.0123
Root relative squared error
0.4259 ± 0.0412
SciMark benchmark
1609.6362