DEVELOPMENT... OpenML
Run
160116

Run 160116

Task 3759 (Supervised Classification) fri_c3_500_25 Uploaded 13-02-2015 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)_I80
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
0.9529
Per class
F measure
0.8679
Per class
Kappa
0.7319
KB relative information score
348.5766
Mean absolute error
0.1541
Mean prior absolute error
0.4928
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
0.8679
Per class
Predictive accuracy
0.868
Prior entropy
0.9897
Recall
0.868
Per class
Relative absolute error
0.3127
Root mean prior squared error
0.4964
Root mean squared error
0.2987
Root relative squared error
0.6018
SciMark benchmark
924.6116
UserCPU time millis
220
UserCPU time millis training
220

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