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Run
175930

Run 175930

Task 264 (Supervised Classification) postoperative-patient-data Uploaded 21-02-2015 by Jason
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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
0.549
Per class
F measure
0.6642
Per class
Kappa
0.1212
KB relative information score
1.3315
Mean absolute error
0.2498
Mean prior absolute error
0.2798
Number of instances
29
Per class
OS information
[Oracle Corporation, 1.7.0_75, amd64, Linux, 3.16.0-29-generic]
Precision
0.6534
Per class
Predictive accuracy
0.6897
Prior entropy
1.0305
Recall
0.6897
Per class
Relative absolute error
0.8926
Root mean prior squared error
0.3657
Root mean squared error
0.4403
Root relative squared error
1.204
SciMark benchmark
1341.2341
UserCPU time millis
10
UserCPU time millis training
10