DEVELOPMENT... OpenML
Run
157603

Run 157603

Task 3021 (Supervised Classification) sick 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
0.973
Per class
F measure
0.9788
Per class
Kappa
0.8155
KB relative information score
2379.0488
Mean absolute error
0.036
Mean prior absolute error
0.1152
Number of instances
3772
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9788
Per class
Predictive accuracy
0.9788
Prior entropy
0.3333
Recall
0.9788
Per class
Relative absolute error
0.3123
Root mean prior squared error
0.2398
Root mean squared error
0.1318
Root relative squared error
0.5498
SciMark benchmark
902.4773
UserCPU time millis
210
UserCPU time millis training
210