DEVELOPMENT... OpenML
Run
47766

Run 47766

Task 94 (Learning Curve) dermatology Uploaded 05-11-2014 by Jason
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  • curves 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
0.9927 ± 0.0066
Per class
Build CPU time
0.0118
Build memory
945998692.4533
F measure
0.9237 ± 0.0423
Per class
Kappa
0.9044 ± 0.0509
KB relative information score
0.8809 ± 0.0344
Mean absolute error
0.0437 ± 0.0093
Mean prior absolute error
0.2664 ± 0.0004
Number of instances
3660
Per class
OS information
[Oracle Corporation, 1.7.0_65, amd64, Linux, 3.5.0-54-generic]
Precision
0.9267 ± 0.0348
Per class
Predictive accuracy
0.924 ± 0.0402
Prior entropy
2.4327 ± 0.0089
Recall
0.924 ± 0.0402
Per class
Relative absolute error
0.1639 ± 0.0347
Root mean prior squared error
0.3649 ± 0.0006
Root mean squared error
0.136 ± 0.0275
Root relative squared error
0.3729 ± 0.0753
SciMark benchmark
1771.6524