DEVELOPMENT... OpenML
Run
157433

Run 157433

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)_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
0.8633
Per class
F measure
0.6358
Per class
Kappa
0.526
KB relative information score
64593.3549
Mean absolute error
0.1386
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
0.6393
Per class
Predictive accuracy
0.6596
Prior entropy
2.2061
Recall
0.6596
Per class
Relative absolute error
0.6552
Root mean prior squared error
0.3252
Root mean squared error
0.2602
Root relative squared error
0.7999
SciMark benchmark
902.4773
UserCPU time millis
11390
UserCPU time millis testing
190
UserCPU time millis training
11200