DEVELOPMENT... OpenML
Run
156928

Run 156928

Task 3591 (Supervised Classification) bank8FM 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
0.9753
Per class
F measure
0.9188
Per class
Kappa
0.8307
KB relative information score
5958.6438
Mean absolute error
0.1424
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
0.919
Per class
Predictive accuracy
0.9191
Prior entropy
0.9731
Recall
0.9191
Per class
Relative absolute error
0.2958
Root mean prior squared error
0.4906
Root mean squared error
0.2469
Root relative squared error
0.5032
SciMark benchmark
929.566
UserCPU time millis
230
UserCPU time millis testing
10
UserCPU time millis training
220