disc.mentr: Discretization using the minimum entropy criterion

In dprep: Data Pre-Processing and Visualization Functions for Classification

Description

This function discretizes the continuous attributes of a data frame using the minumum entropy criterion along with the minimum description length as stopping rule.

Usage

disc.mentr(data, varcon,out=c("symb","num"))

Arguments

data	The name of the dataset to be discretized
varcon	A vector containing the indices of the columms to be discretized
out	To get the data discretized in numerical form enter "num". To get the data discretized in interval form enter "symb"

Value

Returns a matrix containing only discretized features.

Author(s)

Luis Daza(2006) and Edgar Acuna(2015)

References

Dougherty, J., Kohavi, R., and Sahami, M. (1995). Supervised and unsupervised discretization of continuous features. ML-95.

See Also

disc.1r, disc.ew,disc.ef,chiMerge

Examples

## Not run: 
#----Discretization using the entropy with Minimum Description Length.
data(bupa)
bupa.disc=disc.mentr(bupa,1:6,out="num")

## End(Not run)

Example output

Warning messages:
1: In rgl.init(initValue, onlyNULL) : RGL: unable to open X11 display
2: 'rgl_init' failed, running with rgl.useNULL = TRUE 
3: .onUnload failed in unloadNamespace() for 'rgl', details:
  call: fun(...)
  error: object 'rgl_quit' not found 
The number of partitions for var 1   is : 1 
The cut points are: [1] 0
The number of partitions for var 2   is : 1 
The cut points are: [1] 0
The number of partitions for var 3   is : 1 
The cut points are: [1] 0
The number of partitions for var 4   is : 1 
The cut points are: [1] 0
The number of partitions for var 5   is : 2 
The cut points are: [1] 20.5
The number of partitions for var 6   is : 1 
The cut points are: [1] 0

dprep documentation built on May 29, 2017, 11:01 a.m.