DEVELOPMENT... OpenML
Run
160888

Run 160888

Task 3574 (Supervised Classification) rmftsa_sleepdata Uploaded 15-02-2015 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)_I160
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
0.67
Per class
F measure
0.4108
Per class
Kappa
0.1891
KB relative information score
191.8918
Mean absolute error
0.3111
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
0.3982
Per class
Predictive accuracy
0.4629
Prior entropy
1.8507
Recall
0.4629
Per class
Relative absolute error
0.8851
Root mean prior squared error
0.4191
Root mean squared error
0.4059
Root relative squared error
0.9683
SciMark benchmark
936.6206
UserCPU time millis
360
UserCPU time millis training
360