Run
464181

Run 464181

Task 241 (Supervised Classification) balance-scale Uploaded 10-07-2015 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
0.84
Per class
Cross-validation details (33% Holdout set)
F measure
0.6935
Per class
Cross-validation details (33% Holdout set)
Kappa
0.5193
Cross-validation details (33% Holdout set)
KB relative information score
69.5953
Cross-validation details (33% Holdout set)
Mean absolute error
0.2637
Cross-validation details (33% Holdout set)
Mean prior absolute error
0.3857
Cross-validation details (33% Holdout set)
Number of instances
206
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
0.6787
Per class
Cross-validation details (33% Holdout set)
Predictive accuracy
0.733
Cross-validation details (33% Holdout set)
Prior entropy
1.3212
Cross-validation details (33% Holdout set)
Recall
0.733
Per class
Cross-validation details (33% Holdout set)
Relative absolute error
0.6836
Cross-validation details (33% Holdout set)
Root mean prior squared error
0.4424
Cross-validation details (33% Holdout set)
Root mean squared error
0.3531
Cross-validation details (33% Holdout set)
Root relative squared error
0.7982
Cross-validation details (33% Holdout set)
SciMark benchmark
927.2917
UserCPU time millis
250
Cross-validation details (33% Holdout set)
UserCPU time millis testing
10
UserCPU time millis training
240
Cross-validation details (33% Holdout set)