DEVELOPMENT... OpenML
Run
157227

Run 157227

Task 3887 (Supervised Classification) analcatdata_germangss 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
0.9438
Per class
F measure
0.8837
Per class
Kappa
0.6571
KB relative information score
183.4933
Mean absolute error
0.1872
Mean prior absolute error
0.3495
Number of instances
400
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8835
Per class
Predictive accuracy
0.8875
Prior entropy
0.7716
Recall
0.8875
Per class
Relative absolute error
0.5356
Root mean prior squared error
0.4176
Root mean squared error
0.2847
Root relative squared error
0.6817
SciMark benchmark
931.2336
UserCPU time millis
10
UserCPU time millis training
10