Run
46791

Run 46791

Task 1713 (Learning Curve) mfeat-fourier Uploaded 04-11-2014 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_RandomTree(2)Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
weka.RandomTree(2)_K0
weka.RandomTree(2)_M1.0
weka.RandomTree(2)_S1
weka.RandomTree(2)_V0.001
weka.MultiBoostAB_RandomTree(2)_C3
weka.MultiBoostAB_RandomTree(2)_P100
weka.MultiBoostAB_RandomTree(2)_S1
weka.MultiBoostAB_RandomTree(2)_I10
weka.MultiBoostAB_RandomTree(2)_Wweka.classifiers.trees.RandomTree

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
0.8194 ± 0.0214
Per class
Build CPU time
0.0109
Build memory
264981179.4182
F measure
0.6755 ± 0.041
Per class
Kappa
0.6389 ± 0.0428
KB relative information score
0.6601 ± 0.0403
Mean absolute error
0.065 ± 0.0077
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
0.6767 ± 0.0458
Per class
Predictive accuracy
0.675 ± 0.0385
Prior entropy
3.3219
Recall
0.675 ± 0.0385
Per class
Relative absolute error
0.3611 ± 0.0428
Root mean prior squared error
0.3
Root mean squared error
0.255 ± 0.015
Root relative squared error
0.8498 ± 0.0501
SciMark benchmark
1591.1066