DEVELOPMENT... OpenML
Run
161118

Run 161118

Task 3800 (Supervised Classification) fri_c3_500_50 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
0.927
Per class
F measure
0.8372
Per class
Kappa
0.668
KB relative information score
328.1056
Mean absolute error
0.1718
Mean prior absolute error
0.4918
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
0.838
Per class
Predictive accuracy
0.838
Prior entropy
0.9882
Recall
0.838
Per class
Relative absolute error
0.3494
Root mean prior squared error
0.4959
Root mean squared error
0.3351
Root relative squared error
0.6758
SciMark benchmark
933.8635
UserCPU time millis
1130
UserCPU time millis training
1130