DEVELOPMENT... OpenML
Run
157696

Run 157696

Task 1720 (Learning Curve) car Uploaded 12-02-2015 by Jason
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
  • study_2 study_37 weka weka_3.7.12
Issue #Downvotes for this reason By


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
0.9758 ± 0.01
Per class
F measure
0.8482 ± 0.0237
Per class
Kappa
0.6703 ± 0.0567
KB relative information score
0.5834 ± 0.0258
Mean absolute error
0.1137 ± 0.0059
Mean prior absolute error
0.229 ± 0.0007
Number of instances
1728
Per class
OS information
[Oracle Corporation, 1.7.0_75, amd64, Linux, 3.16.0-29-generic]
Precision
0.8523 ± 0.0219
Per class
Predictive accuracy
0.8565 ± 0.0229
Prior entropy
1.2058 ± 0.0093
Recall
0.8565 ± 0.0229
Per class
Relative absolute error
0.4965 ± 0.026
Root mean prior squared error
0.3381 ± 0.001
Root mean squared error
0.2261 ± 0.0071
Root relative squared error
0.6688 ± 0.0217
SciMark benchmark
646.4525
UserCPU time millis
20
UserCPU time millis training
20