Run
54298

Run 54298

Task 2102 (Learning Curve) eucalyptus Uploaded 08-11-2014 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.Bagging_REPTree(3)Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
weka.Bagging_REPTree(3)_I10
weka.Bagging_REPTree(3)_P100
weka.Bagging_REPTree(3)_S1
weka.Bagging_REPTree(3)_Wweka.classifiers.trees.REPTree
weka.Bagging_REPTree(3)_num-slots1
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

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
0.7642 ± 0.0318
Per class
Build CPU time
0.0166
Build memory
3131979378.2
F measure
0.4442 ± 0.0456
Per class
Kappa
0.2903 ± 0.0553
KB relative information score
0.348 ± 0.0382
Mean absolute error
0.2348 ± 0.0124
Mean prior absolute error
0.3132 ± 0.0002
Number of instances
736
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.4438 ± 0.0503
Per class
Predictive accuracy
0.4511 ± 0.0447
Prior entropy
2.2621 ± 0.0043
Recall
0.4511 ± 0.0447
Per class
Relative absolute error
0.7497 ± 0.0395
Root mean prior squared error
0.3957 ± 0.0003
Root mean squared error
0.3729 ± 0.0141
Root relative squared error
0.9424 ± 0.0357
SciMark benchmark
1615.5755