Run
175929

Run 175929

Task 265 (Supervised Classification) dermatology Uploaded 21-02-2015 by Jan van Rijn
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Flow

weka.PART(3)Eibe Frank, Ian H. Witten: Generating Accurate Rule Sets Without Global Optimization. In: Fifteenth International Conference on Machine Learning, 144-151, 1998.
weka.PART(3)_C0.25
weka.PART(3)_M2
weka.PART(3)_Q1

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
0.9752
Per class
Cross-validation details (33% Holdout set)
F measure
0.9498
Per class
Cross-validation details (33% Holdout set)
Kappa
0.9365
Cross-validation details (33% Holdout set)
KB relative information score
110.1281
Cross-validation details (33% Holdout set)
Mean absolute error
0.0225
Cross-validation details (33% Holdout set)
Mean prior absolute error
0.2653
Cross-validation details (33% Holdout set)
Number of instances
120
Per class
Cross-validation details (33% Holdout set)
OS information
[Oracle Corporation, 1.7.0_75, amd64, Linux, 3.16.0-29-generic]
Precision
0.9516
Per class
Cross-validation details (33% Holdout set)
Predictive accuracy
0.95
Cross-validation details (33% Holdout set)
Prior entropy
2.4378
Cross-validation details (33% Holdout set)
Recall
0.95
Per class
Cross-validation details (33% Holdout set)
Relative absolute error
0.085
Cross-validation details (33% Holdout set)
Root mean prior squared error
0.3633
Cross-validation details (33% Holdout set)
Root mean squared error
0.1222
Cross-validation details (33% Holdout set)
Root relative squared error
0.3364
Cross-validation details (33% Holdout set)
SciMark benchmark
1384.4418
UserCPU time millis
10
UserCPU time millis training
10