Run
247990

Run 247990

Task 3796 (Supervised Classification) fri_c4_250_25 Uploaded 04-03-2015 by Joaquin Vanschoren
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Flow

weka.NaiveBayes(10)George H. John, Pat Langley: Estimating Continuous Distributions in Bayesian Classifiers. In: Eleventh Conference on Uncertainty in Artificial Intelligence, San Mateo, 338-345, 1995.

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
0.6857
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.647
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.2875
Cross-validation details (10-fold Crossvalidation)
KB relative information score
52.5282
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.4006
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4962
Cross-validation details (10-fold Crossvalidation)
Number of instances
250
Per class
Cross-validation details (10-fold Crossvalidation)
OS information
[Oracle Corporation, 1.7.0_75, amd64, Linux, 3.16.0-29-generic]
Precision
0.6468
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.648
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9945
Cross-validation details (10-fold Crossvalidation)
Recall
0.648
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.8074
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4981
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.4869
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9776
Cross-validation details (10-fold Crossvalidation)
SciMark benchmark
1339.944
UserCPU time millis training