DEVELOPMENT... OpenML
Run
160920

Run 160920

Task 3605 (Supervised Classification) sleep 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
0.6123
Per class
F measure
0.6129
Per class
Kappa
0.229
KB relative information score
13.8081
Mean absolute error
0.389
Mean prior absolute error
0.498
Number of instances
62
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.618
Per class
Predictive accuracy
0.6129
Prior entropy
0.9972
Recall
0.6129
Per class
Relative absolute error
0.7812
Root mean prior squared error
0.499
Root mean squared error
0.5767
Root relative squared error
1.1559
SciMark benchmark
936.6206
UserCPU time millis
20
UserCPU time millis training
20