DEVELOPMENT... OpenML
Run
157470

Run 157470

Task 230 (Supervised Classification) SEA(50000) 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
0.8717
Per class
F measure
0.8313
Per class
Kappa
0.6405
KB relative information score
450984.3875
Mean absolute error
0.2755
Mean prior absolute error
0.4739
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
0.8337
Per class
Predictive accuracy
0.834
Prior entropy
0.9619
Recall
0.834
Per class
Relative absolute error
0.5813
Root mean prior squared error
0.4868
Root mean squared error
0.3657
Root relative squared error
0.7513
SciMark benchmark
943.2817
UserCPU time millis
42100
UserCPU time millis testing
860
UserCPU time millis training
41240