OpenML
458311

Run 458311

Task 284 (Supervised Classification) hepatitis Uploaded 02-07-2015 by Joaquin Vanschoren
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
Issue #Downvotes for this reason By


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
0.8735
Per class
Cross-validation details (33% Holdout set)
F measure
0.8506
Per class
Cross-validation details (33% Holdout set)
Kappa
0.5863
Cross-validation details (33% Holdout set)
KB relative information score
23.0151
Cross-validation details (33% Holdout set)
Mean absolute error
0.2028
Cross-validation details (33% Holdout set)
Mean prior absolute error
0.3579
Cross-validation details (33% Holdout set)
Number of instances
51
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
0.8642
Per class
Cross-validation details (33% Holdout set)
Predictive accuracy
0.8627
Cross-validation details (33% Holdout set)
Prior entropy
0.7418
Cross-validation details (33% Holdout set)
Recall
0.8627
Per class
Cross-validation details (33% Holdout set)
Relative absolute error
0.5665
Cross-validation details (33% Holdout set)
Root mean prior squared error
0.4381
Cross-validation details (33% Holdout set)
Root mean squared error
0.3353
Cross-validation details (33% Holdout set)
Root relative squared error
0.7654
Cross-validation details (33% Holdout set)
SciMark benchmark
938.5498
UserCPU time millis
270
Cross-validation details (33% Holdout set)
UserCPU time millis training
270
Cross-validation details (33% Holdout set)