DEVELOPMENT... OpenML
Run
156930

Run 156930

Task 3593 (Supervised Classification) 2dplanes 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
0.9197
Per class
F measure
0.8493
Per class
Kappa
0.6987
KB relative information score
21590.6293
Mean absolute error
0.2532
Mean prior absolute error
0.5
Number of instances
40768
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8493
Per class
Predictive accuracy
0.8493
Prior entropy
1
Recall
0.8493
Per class
Relative absolute error
0.5065
Root mean prior squared error
0.5
Root mean squared error
0.3376
Root relative squared error
0.6753
SciMark benchmark
929.566
UserCPU time millis
1610
UserCPU time millis testing
30
UserCPU time millis training
1580