classif {FactoInvestigate}

Classification description

Description

Realise the hierachical ascending classification (HCPC function) of the individuals (or rows) and describe the specifications of each cluster.

Usage

classif(res, file = "", dim = 1:2, nclust = -1, selec = "contrib", coef = 1, 
        mmax = 10, nmax = 10, figure.title = "Figure", graph = TRUE, options = NULL)

Arguments

res

an object of class PCA, CA or MCA.

file

the file path where to write the description in Rmarkdown langage. If not specified, the description is written in the console.

dim

a 2 dimensional numerical vector giving the factorial dimensions to describe (by default the first plane).

nclust

an integer forcing the number of clusters desired. The value -1 return the clustering evaluated as the most appropriate (default).

selec

the selection criterion of individuals to plot on the graph.

coef

a numerical coefficient to adjust the selection rule (exemple : if equals 2, the threshold is 2 times higher, and thus more restrictive)

mmax

an integer giving the maximum number of individuals to illustrate each cluster (by defaut 10).

nmax

an integer giving the maximum number of variables to illustrate each cluster (by defaut 10).

figure.title

the text label to add before graph title.

graph

a boolean : if TRUE, the graph is ploted into the console.

options

a character string that gives the output options for the figures. If NULL, options="r, echo = FALSE, fig.align = 'center', fig.height = 3.5, fig.width = 5.5" for linuw and Mac and options="r, echo = FALSE, fig.height = 3.5, fig.width = 5.5" for Windows

Details

The selec argument is used in order to select a part of the individuals that are drawn and described. For example, you can use either :
- selec = 1:5 then the individuals numbered 1 to 5 are drawn.
- selec = c("name1","name5") then the individuals named name1 and name5 are drawn.
- selec = "contrib 10" then the 10 active or illustrative individuals that have the highest contribution on the 2 dimensions of the plane are drawn.
- selec = "contrib" then the optimal number of active or illustrative individuals that have the highest contribution on the 2 dimensions of the plane are drawn.
- selec = "cos2 5" then the 5 active or illustrative individuals that have the highest cos2 on the 2 dimensions of the plane are drawn.
- selec = "cos2 0.8" then the active or illustrative individuals that have a cos2 higher to 0.8 on the plane are drawn.
- selec = "cos2" then the optimal number of active or illustrative individuals that have the highest cos2 on the 2 dimensions of the plane are drawn.

The coef argument is used in order to adjust the selection of the individuals when based on selec = "contrib" or selec = "cos2". For example :
- if coef = 2, the threshold is 2 times higher, and thus 2 times more restrictive.
- if coef = 0.5, the threshold is 2 times lower, and thus 2 times less restrictive.

Value

res.hcpc

the result of the HCPC function on the dimensions specified.

Author(s)

Simon Thuleau and Francois Husson

See Also

description

Examples

## Not run: 
data(decathlon)
res.pca = PCA(decathlon, quanti.sup = c(11:12), quali.sup = c(13), graph = FALSE)
classif(res.pca, file = "PCA.Rmd")

data(children)
res.ca = CA(children, row.sup = 15:18, col.sup = 6:8, graph = FALSE)
classif(res.ca, file = "CA.Rmd")

data(tea)
res.mca = MCA(tea, quanti.sup = 19,quali.sup = 20:36, graph = FALSE)
classif(res.mca, file = "MCA.Rmd")

## End(Not run)