DEVELOPMENT... OpenML
Run
159974

Run 159974

Task 3591 (Supervised Classification) bank8FM Uploaded 13-02-2015 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)_I80
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
0.9886
Per class
F measure
0.9418
Per class
Kappa
0.879
KB relative information score
6874.6457
Mean absolute error
0.0812
Mean prior absolute error
0.4815
Number of instances
8192
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9418
Per class
Predictive accuracy
0.9419
Prior entropy
0.9731
Recall
0.9419
Per class
Relative absolute error
0.1687
Root mean prior squared error
0.4906
Root mean squared error
0.2044
Root relative squared error
0.4166
SciMark benchmark
924.6116
UserCPU time millis
1660
UserCPU time millis training
1660