GMVEBSWiMS {FRESA.CAD}

Hybrid Hierarchical Modeling with GMVE and BSWiMS

Description

This function returns the BSWiMS supervised-classifier present at each one of the GMVE unsupervised Gaussian data clusters

Usage

   GMVEBSWiMS(formula = formula,
            data=NULL,
            GMVE.control = list(p.threshold = 0.95,p.samplingthreshold = 0.5),
            ...
   )

Arguments

formula

An object of class formula with the formula to be fitted

data

A data frame where all variables are stored in different columns

GMVE.control

Control parameters of the GMVECluster function

...

Parameters to be passed to the BSWiMS.model function

Details

First, the function calls the BSWiMS function that returns the relevant features associated with the outcome. Then, it calls the GMVE clustering algorithm (GMVECluster) that returns a relevant data partition based on Gaussian clusters. Finally, the function will execute the BSWiMS.model classification function on each cluster returned by GMVECluster.

Value

features

The character vector with the releavant BSWiMS features.

cluster

The GMVECluster object

models

The list of BSWiMS.model models per cluster

Author(s)

Jose G. Tamez-Pena

Examples

   ## Not run: 
   # Get the Sonar data set
      library(mlbench)
      data(Sonar)
      Sonar$Class <- 1*(Sonar$Class == "M")
     #Train hierachical classifier
      mc <- GMVEBSWiMS(Class~.,Sonar)
     #report the classification
      pb <- predict(mc,Sonar)
      print(table(1*(pb>0.0),Sonar$Class))
   
## End(Not run)