DEVELOPMENT... OpenML
Run
157990

Run 157990

Task 3630 (Supervised Classification) analcatdata_apnea3 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)_I20
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
0.9174
Per class
F measure
0.9035
Per class
Kappa
0.536
KB relative information score
156.8417
Mean absolute error
0.1236
Mean prior absolute error
0.2158
Number of instances
450
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9013
Per class
Predictive accuracy
0.9067
Prior entropy
0.5405
Recall
0.9067
Per class
Relative absolute error
0.5728
Root mean prior squared error
0.3275
Root mean squared error
0.2398
Root relative squared error
0.7321
SciMark benchmark
947.9494
UserCPU time millis
10
UserCPU time millis training
10