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Run
156859

Run 156859

Task 2263 (Supervised Classification) BNG(vehicle) 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
0.8661
Per class
F measure
0.6278
Per class
Kappa
0.5243
KB relative information score
437773.9123
Mean absolute error
0.2535
Mean prior absolute error
0.3748
Number of instances
1000000
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.6259
Per class
Predictive accuracy
0.6431
Prior entropy
1.9991
Recall
0.6431
Per class
Relative absolute error
0.6762
Root mean prior squared error
0.4329
Root mean squared error
0.3424
Root relative squared error
0.7909
SciMark benchmark
932.3943
UserCPU time millis
563510
UserCPU time millis testing
1310
UserCPU time millis training
562200