DEVELOPMENT... OpenML
Run
50500

Run 50500

Task 1711 (Learning Curve) mfeat-factors Uploaded 06-11-2014 by Jason
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  • study_2 study_37 weka weka_3.7.12-SNAPSHOT
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Flow

weka.LWL_RandomTree(2)Eibe Frank, Mark Hall, Bernhard Pfahringer: Locally Weighted Naive Bayes. In: 19th Conference in Uncertainty in Artificial Intelligence, 249-256, 2003. C. Atkeson, A. Moore, S. Schaal (1996). Locally weighted learning. AI Review..
weka.RandomTree(2)_K0
weka.RandomTree(2)_M1.0
weka.RandomTree(2)_S1
weka.RandomTree(2)_V0.001
weka.LWL_RandomTree(2)_Atrue
weka.LWL_RandomTree(2)_K-1
weka.LWL_RandomTree(2)_U0
weka.LWL_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
0.9253 ± 0.0139
Per class
Build CPU time
0.0001
Build memory
161316895.6364
F measure
0.865 ± 0.026
Per class
Kappa
0.85 ± 0.0288
KB relative information score
0.859 ± 0.0266
Mean absolute error
0.027 ± 0.0051
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
0.8655 ± 0.0252
Per class
Predictive accuracy
0.865 ± 0.0259
Prior entropy
3.3219
Recall
0.865 ± 0.0259
Per class
Relative absolute error
0.15 ± 0.0285
Root mean prior squared error
0.3
Root mean squared error
0.164 ± 0.0155
Root relative squared error
0.5468 ± 0.0516
SciMark benchmark
1708.8151