DEVELOPMENT... OpenML
Run
159263

Run 159263

Task 3631 (Supervised Classification) analcatdata_apnea2 Uploaded 12-02-2015 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)_I40
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
0.947
Per class
F measure
0.9482
Per class
Kappa
0.7815
KB relative information score
266.8346
Mean absolute error
0.0958
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
0.9494
Per class
Predictive accuracy
0.9474
Prior entropy
0.5744
Recall
0.9474
Per class
Relative absolute error
0.4091
Root mean prior squared error
0.3414
Root mean squared error
0.2045
Root relative squared error
0.5989
SciMark benchmark
924.6116
UserCPU time millis
20
UserCPU time millis testing
10
UserCPU time millis training
10