Run
287444

Run 287444

Task 272 (Supervised Classification) haberman Uploaded 13-03-2015 by Joaquin Vanschoren
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Flow

weka.BFTree(3)Haijian Shi (2007). Best-first decision tree learning. Hamilton, NZ. Jerome Friedman, Trevor Hastie, Robert Tibshirani (2000). Additive logistic regression : A statistical view of boosting. Annals of statistics. 28(2):337-407.
weka.BFTree(3)_PPOSTPRUNED
weka.BFTree(3)_M2
weka.BFTree(3)_N5
weka.BFTree(3)_Ctrue
weka.BFTree(3)_S1

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
0.5528
Per class
Cross-validation details (33% Holdout set)
F measure
0.6972
Per class
Cross-validation details (33% Holdout set)
Kappa
0.1959
Cross-validation details (33% Holdout set)
KB relative information score
17.7339
Cross-validation details (33% Holdout set)
Mean absolute error
0.3064
Cross-validation details (33% Holdout set)
Mean prior absolute error
0.3925
Cross-validation details (33% Holdout set)
Number of instances
100
Per class
Cross-validation details (33% Holdout set)
OS information
[Oracle Corporation, 1.7.0_75, amd64, Linux, 3.16.0-29-generic]
Precision
0.69
Per class
Cross-validation details (33% Holdout set)
Predictive accuracy
0.72
Cross-validation details (33% Holdout set)
Prior entropy
0.836
Cross-validation details (33% Holdout set)
Recall
0.72
Per class
Cross-validation details (33% Holdout set)
Relative absolute error
0.7807
Cross-validation details (33% Holdout set)
Root mean prior squared error
0.444
Cross-validation details (33% Holdout set)
Root mean squared error
0.4691
Cross-validation details (33% Holdout set)
Root relative squared error
1.0566
Cross-validation details (33% Holdout set)
SciMark benchmark
1340.1351
UserCPU time millis
10
UserCPU time millis training
10