DEVELOPMENT... OpenML
Run
157965

Run 157965

Task 3607 (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
0.7785
Per class
F measure
0.7161
Per class
Kappa
0.4387
KB relative information score
295.2748
Mean absolute error
0.3709
Mean prior absolute error
0.5
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
0.7306
Per class
Predictive accuracy
0.7197
Prior entropy
1
Recall
0.7197
Per class
Relative absolute error
0.7417
Root mean prior squared error
0.5
Root mean squared error
0.4369
Root relative squared error
0.8739
SciMark benchmark
947.9494
UserCPU time millis
10
UserCPU time millis training
10