DEVELOPMENT... OpenML
Run
157744

Run 157744

Task 2102 (Learning Curve) eucalyptus Uploaded 12-02-2015 by Jason
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  • study_2 study_37 weka weka_3.7.12
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Flow

weka.HoeffdingTree(3)Geoff Hulten, Laurie Spencer, Pedro Domingos: Mining time-changing data streams. In: ACM SIGKDD Intl. Conf. on Knowledge Discovery and Data Mining, 97-106, 2001.
weka.HoeffdingTree(3)_L2
weka.HoeffdingTree(3)_S1
weka.HoeffdingTree(3)_E1.0E-7
weka.HoeffdingTree(3)_H0.05
weka.HoeffdingTree(3)_M0.01
weka.HoeffdingTree(3)_G200.0
weka.HoeffdingTree(3)_N0.0

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.

22 Evaluation measures

Area under ROC curve
0.853 ± 0.0235
Per class
F measure
0.5284 ± 0.055
Per class
Kappa
0.3987 ± 0.0661
KB relative information score
0.4596 ± 0.046
Mean absolute error
0.1888 ± 0.0157
Mean prior absolute error
0.3132 ± 0.0002
Number of instances
736
Per class
OS information
[Oracle Corporation, 1.7.0_75, amd64, Linux, 3.16.0-29-generic]
Precision
0.6034 ± 0.0564
Per class
Predictive accuracy
0.5313 ± 0.0515
Prior entropy
2.2621 ± 0.0043
Recall
0.5313 ± 0.0515
Per class
Relative absolute error
0.6027 ± 0.05
Root mean prior squared error
0.3957 ± 0.0003
Root mean squared error
0.3868 ± 0.0184
Root relative squared error
0.9774 ± 0.0467
SciMark benchmark
646.4525
UserCPU time millis
60
UserCPU time millis testing
30
UserCPU time millis training
30