DEVELOPMENT... OpenML
Run
156714

Run 156714

Task 202 (Supervised Classification) BNG(glass,nominal,137781) 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
0.8575
Per class
F measure
0.6201
Per class
Kappa
0.5094
KB relative information score
61703.3588
Mean absolute error
0.1436
Mean prior absolute error
0.2115
Number of instances
137781
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.6283
Per class
Predictive accuracy
0.6499
Prior entropy
2.2061
Recall
0.6499
Per class
Relative absolute error
0.6787
Root mean prior squared error
0.3252
Root mean squared error
0.2625
Root relative squared error
0.8072
SciMark benchmark
923.9763
UserCPU time millis
5620
UserCPU time millis testing
180
UserCPU time millis training
5440