DEVELOPMENT... OpenML
Run
159911

Run 159911

Task 3530 (Supervised Classification) re1.wc 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)_I40
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
0.9827
Per class
F measure
0.8685
Per class
Kappa
0.8565
KB relative information score
1409.7758
Mean absolute error
0.012
Mean prior absolute error
0.071
Number of instances
1657
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8685
Per class
Predictive accuracy
0.8739
Prior entropy
3.8125
Recall
0.8739
Per class
Relative absolute error
0.1697
Root mean prior squared error
0.1883
Root mean squared error
0.0911
Root relative squared error
0.4836
SciMark benchmark
917.712
UserCPU time millis
4848340
UserCPU time millis testing
10
UserCPU time millis training
4848330