Flow
weka.LogitBoost_REPTree

weka.LogitBoost_REPTree

Visibility: public Uploaded 05-12-2014 by Richie Brondenstein Weka_3.7.12-SNAPSHOT 0 runs
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
Issue #Downvotes for this reason By


Loading wiki
Help us complete this description Edit
J. Friedman, T. Hastie, R. Tibshirani (1998). Additive Logistic Regression: a Statistical View of Boosting. Stanford University.

Components

Wweka.REPTree(6)Full name of base classifier. (default: weka.classifiers.trees.DecisionStump)

Parameters

-do-not-check-capabilitiesIf set, classifier capabilities are not checked before classifier is built (use with caution).
EThe number of threads to use for batch prediction, which should be >= size of thread pool. (default 1)default: 1
HShrinkage parameter. (default 1)default: 1.0
INumber of iterations. (default 10)default: 10
LThreshold on the improvement of the likelihood. (default -Double.MAX_VALUE)default: -1.7976931348623157E308
OThe size of the thread pool, for example, the number of cores in the CPU. (default 1)default: 1
PPercentage of weight mass to base training on. (default 100, reduce to around 90 speed up)default: 100
QUse resampling instead of reweighting for boosting.
SRandom number seed. (default 1)default: 1
WFull name of base classifier. (default: weka.classifiers.trees.DecisionStump)default: weka.classifiers.trees.REPTree
ZZ max threshold for responses. (default 3)default: 3.0
output-debug-infoIf set, classifier is run in debug mode and may output additional info to the console

0
Runs

List all runs
Parameter:
Rendering chart
Rendering table