DEVELOPMENT... OpenML
Run
157082

Run 157082

Task 3743 (Supervised Classification) fri_c2_500_25 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)_I10
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
0.91
Per class
F measure
0.8331
Per class
Kappa
0.6482
KB relative information score
254.082
Mean absolute error
0.2498
Mean prior absolute error
0.4768
Number of instances
500
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.833
Per class
Predictive accuracy
0.834
Prior entropy
0.9664
Recall
0.834
Per class
Relative absolute error
0.5239
Root mean prior squared error
0.4882
Root mean squared error
0.3381
Root relative squared error
0.6926
SciMark benchmark
929.566
UserCPU time millis
30
UserCPU time millis training
30