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weka.LogitBoost_REPTree

Visibility: public Uploaded 02-12-2015 by Thomas Clark Weka_3.7.13 1 runs
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J. Friedman, T. Hastie, R. Tibshirani (1998). Additive Logistic Regression: a Statistical View of Boosting. Stanford University.

Components

Full name of base classifier. (default: weka.classifiers.trees.DecisionStump)

-do-not-check-capabilities	If set, classifier capabilities are not checked before classifier is built (use with caution).
E	The number of threads to use for batch prediction, which should be >= size of thread pool. (default 1)	default: 1
H	Shrinkage parameter. (default 1)	default: 1.0
I	Number of iterations. (default 10)	default: 10
L	Threshold on the improvement of the likelihood. (default -Double.MAX_VALUE)	default: -1.7976931348623157E308
O	The size of the thread pool, for example, the number of cores in the CPU. (default 1)	default: 1
P	Percentage of weight mass to base training on. (default 100, reduce to around 90 speed up)	default: 100
Q	Use resampling instead of reweighting for boosting.
S	Random number seed. (default 1)	default: 1
W	Full name of base classifier. (default: weka.classifiers.trees.DecisionStump)	default: weka.classifiers.trees.REPTree
Z	Z max threshold for responses. (default 3)	default: 3.0
num-decimal-places	The number of decimal places for the output of numbers in the model (default 2).
output-debug-info	If set, classifier is run in debug mode and may output additional info to the console

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