DEVELOPMENT... OpenML
Run
157370

Run 157370

Task 6 (Supervised Classification) letter Uploaded 11-02-2015 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
0.9855
Per class
F measure
0.7947
Per class
Kappa
0.7863
KB relative information score
15729.2386
Mean absolute error
0.0269
Mean prior absolute error
0.074
Number of instances
20000
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.7966
Per class
Predictive accuracy
0.7946
Prior entropy
4.6998
Recall
0.7946
Per class
Relative absolute error
0.363
Root mean prior squared error
0.1923
Root mean squared error
0.1067
Root relative squared error
0.555
SciMark benchmark
940.2922
UserCPU time millis
45550
UserCPU time millis testing
90
UserCPU time millis training
45460