DEVELOPMENT... OpenML
Run
159304

Run 159304

Task 3679 (Supervised Classification) chscase_vine2 Uploaded 12-02-2015 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
0.9019
Per class
F measure
0.8375
Per class
Kappa
0.6721
KB relative information score
240.4964
Mean absolute error
0.2556
Mean prior absolute error
0.4956
Number of instances
468
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8375
Per class
Predictive accuracy
0.8376
Prior entropy
0.9937
Recall
0.8376
Per class
Relative absolute error
0.5158
Root mean prior squared error
0.4978
Root mean squared error
0.3532
Root relative squared error
0.7095
SciMark benchmark
945.6434
UserCPU time millis
20
UserCPU time millis training
20