RFfit: Fit random forest model

In david-salgado/categObsPredModelParam: Class and methods for the parameters of a categorical observation- prediction model

Description

RFfit fits a random forest model for a specific value of the regressand and specific regressors. Return an object of class randomForest.

Usage

RFfit(data, targetVarName, parms, regressors)

Arguments

data	data frame, list or environment (or object coercible by as.data.table to a data.table) containing the variables in the model (see 'Details').
targetVarName	value of the regressand (an object of class character).
parms	names of the identification variables for every unit in the input data set data.
regressors	an object of class character containing the design weight.

Value

an object of class randomForest with model fit.

Examples

## Not run: 
  fitPar <- new(Class = 'fitParam',
  edData = FFall_AS.StQ, rawData = FGall_AS.StQ, 
  selParam = list(ntreeTry=1000, stepFactor=2, improve=0.05, 
                  trace=TRUE, plot=TRUE, doBest = TRUE, 
                  ptrain = 0.8, DD = DDactu),
                  valParam = list(edEffInd = effInd, priorBin = 5, 
                  dataVal = c('Train','Test')))
                  
 ObsPredPar1 <- new(Class = 'categObsPredModelParam',
                  Data = FGall_AS.StQ,
                  VarRoles = list(Units = IDUnits,
                  Domains = character(0),
                  DesignW = DesignW,
                  Regressands = Regressands,
                  Regressors = Regressors
                  ))
                  
ObsPredPar1 <-  fitModels(ObsPredPar1, fitPar, na.as.category)

## End(Not run)

david-salgado/categObsPredModelParam documentation built on Dec. 3, 2020, 1:42 p.m.