DEVELOPMENT... OpenML
Run
158881

Run 158881

Task 137 (Supervised Classification) BNG(autos,nominal,1000000) Uploaded 12-02-2015 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)_I40
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
0.9355
Per class
F measure
0.7368
Per class
Kappa
0.6631
KB relative information score
621462.7973
Mean absolute error
0.1076
Mean prior absolute error
0.221
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
0.7378
Per class
Predictive accuracy
0.7423
Prior entropy
2.3035
Recall
0.7423
Per class
Relative absolute error
0.4868
Root mean prior squared error
0.3324
Root mean squared error
0.2265
Root relative squared error
0.6813
SciMark benchmark
931.2336
UserCPU time millis
471730
UserCPU time millis testing
1540
UserCPU time millis training
470190