boosting: Applies the AdaBoost.M1 and SAMME algorithms to a data set

In Fuzzy-Logix/AdapteR: Converts R syntax to SQL to provide fast analytics using in-database C++ library DB Lytix.

Description

Fits the AdaBoost.M1 (Freund and Schapire, 1996) and SAMME (Zhu et al., 2009) algorithms using classification trees as single classifiers.

Usage

boosting(formula, data, ...)

Arguments

formula	formula specifying the independent and dependent variable columns
data	FLTable
mfinal	an integer, the number of iterations for which boosting is run or the number of trees to use. Defaults to mfinal=10 iterations.
control	options that control details of the rpart algorithm. See rpart for more details.

Value

An object of class "FLBoosting" which has details about the trees generated and the number of votes in bag corresponding to every ObsID.

See Also

boosting for corresponding R function reference.

Examples

flt <- FLTable(getTestTableName("tblBoostDT"),
             "ObsID","VarID","Num_Val")
flobj <- boosting(flt, formula = -1~.,mfinal=10)
pred <- predict(flobj, newdata= flt[1:200, 1:18])
pred$confusion
pred$class

Fuzzy-Logix/AdapteR documentation built on May 6, 2019, 5:07 p.m.