DEVELOPMENT... OpenML
Run
157931

Run 157931

Task 3574 (Supervised Classification) rmftsa_sleepdata 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
0.6804
Per class
F measure
0.404
Per class
Kappa
0.1983
KB relative information score
182.3442
Mean absolute error
0.3122
Mean prior absolute error
0.3514
Number of instances
1024
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.4201
Per class
Predictive accuracy
0.4756
Prior entropy
1.8507
Recall
0.4756
Per class
Relative absolute error
0.8883
Root mean prior squared error
0.4191
Root mean squared error
0.3987
Root relative squared error
0.9514
SciMark benchmark
947.9494
UserCPU time millis
50
UserCPU time millis training
50