DEVELOPMENT... OpenML
Run
157694

Run 157694

Task 1717 (Learning Curve) mfeat-morphological 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
0.9482 ± 0.0058
Per class
F measure
0.62 ± 0.0269
Per class
Kappa
0.615 ± 0.0244
KB relative information score
0.6906 ± 0.0214
Mean absolute error
0.0715 ± 0.0027
Mean prior absolute error
0.18
Number of instances
2000
Per class
OS information
[Oracle Corporation, 1.7.0_75, amd64, Linux, 3.16.0-29-generic]
Precision
0.6468 ± 0.0387
Per class
Predictive accuracy
0.6535 ± 0.022
Prior entropy
3.3219
Recall
0.6535 ± 0.022
Per class
Relative absolute error
0.3974 ± 0.015
Root mean prior squared error
0.3
Root mean squared error
0.2257 ± 0.0083
Root relative squared error
0.7522 ± 0.0276
SciMark benchmark
642.8724
UserCPU time millis
230
UserCPU time millis testing
80
UserCPU time millis training
150