DEVELOPMENT... OpenML
Run
156969

Run 156969

Task 3631 (Supervised Classification) analcatdata_apnea2 Uploaded 11-02-2015 by Felicia West
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Flow

weka.LogitBoost_DecisionStump(2)J. Friedman, T. Hastie, R. Tibshirani (1998). Additive Logistic Regression: a Statistical View of Boosting. Stanford University.
weka.LogitBoost_DecisionStump(2)_E1
weka.LogitBoost_DecisionStump(2)_H1.0
weka.LogitBoost_DecisionStump(2)_I10
weka.LogitBoost_DecisionStump(2)_L-1.7976931348623157E308
weka.LogitBoost_DecisionStump(2)_O1
weka.LogitBoost_DecisionStump(2)_P100
weka.LogitBoost_DecisionStump(2)_S1
weka.LogitBoost_DecisionStump(2)_Wweka.classifiers.trees.DecisionStump
weka.LogitBoost_DecisionStump(2)_Z3.0

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
0.9384
Per class
F measure
0.9391
Per class
Kappa
0.7399
KB relative information score
250.1938
Mean absolute error
0.1149
Mean prior absolute error
0.2343
Number of instances
475
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9394
Per class
Predictive accuracy
0.9389
Prior entropy
0.5744
Recall
0.9389
Per class
Relative absolute error
0.4905
Root mean prior squared error
0.3414
Root mean squared error
0.2111
Root relative squared error
0.6182
SciMark benchmark
931.2336
UserCPU time millis
10
UserCPU time millis training
10