Run
386980

Run 386980

Task 282 (Supervised Classification) heart-statlog Uploaded 05-04-2015 by Joaquin Vanschoren
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Flow

weka.NBTree(3)Ron Kohavi: Scaling Up the Accuracy of Naive-Bayes Classifiers: A Decision-Tree Hybrid. In: Second International Conference on Knoledge Discovery and Data Mining, 202-207, 1996.

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
0.8316
Per class
Cross-validation details (33% Holdout set)
F measure
0.7737
Per class
Cross-validation details (33% Holdout set)
Kappa
0.548
Cross-validation details (33% Holdout set)
KB relative information score
44.9523
Cross-validation details (33% Holdout set)
Mean absolute error
0.2554
Cross-validation details (33% Holdout set)
Mean prior absolute error
0.4981
Cross-validation details (33% Holdout set)
Number of instances
89
Per class
Cross-validation details (33% Holdout set)
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.7794
Per class
Cross-validation details (33% Holdout set)
Predictive accuracy
0.7753
Cross-validation details (33% Holdout set)
Prior entropy
0.9912
Cross-validation details (33% Holdout set)
Recall
0.7753
Per class
Cross-validation details (33% Holdout set)
Relative absolute error
0.5128
Cross-validation details (33% Holdout set)
Root mean prior squared error
0.5012
Cross-validation details (33% Holdout set)
Root mean squared error
0.425
Cross-validation details (33% Holdout set)
Root relative squared error
0.8481
Cross-validation details (33% Holdout set)
SciMark benchmark
946.9304
UserCPU time millis
210
Cross-validation details (33% Holdout set)
UserCPU time millis testing
10
UserCPU time millis training
200
Cross-validation details (33% Holdout set)