DEVELOPMENT... OpenML
Run
159818

Run 159818

Task 3534 (Supervised Classification) ohscal.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)_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
0.9624
Per class
F measure
0.7632
Per class
Kappa
0.7336
KB relative information score
7792.3409
Mean absolute error
0.0729
Mean prior absolute error
0.1787
Number of instances
11162
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.7662
Per class
Predictive accuracy
0.7619
Prior entropy
3.2759
Recall
0.7619
Per class
Relative absolute error
0.4078
Root mean prior squared error
0.2989
Root mean squared error
0.1863
Root relative squared error
0.6231
SciMark benchmark
938.9865
UserCPU time millis
13098750
UserCPU time millis testing
40
UserCPU time millis training
13098710