discretization (version 1.0-1.1)

cacc: Auxiliary function for CACC discretization algorithm

Description

This function is requied to compute the cacc value for CACC discretization algorithm.

Usage

cacc(tb)

Arguments

tb

a vector of observed frequencies

Value

val

numeric of cacc value

Details

The Class-Attribute Contingency Coefficient(CACC) discretization algorithm implements in disc.Topdown(data,method=2).

The cacc value is defined as $$cacc = \sqrt{\frac{y}{y+M}}$$ for $$y = \chi^2/log(n)$$ \(M\) is the total number of samples, \(n\) is a number of discretized intervals. This value calculates in contingency table between class variable and discrete interval, row matrix representing the class variable and each column of discrete interval.

References

Tsai, C. J., Lee, C. I. and Yang, W. P. (2008). A discretization algorithm based on Class-Attribute Contingency Coefficient, Information Sciences, 178, 714--731.

See Also

disc.Topdown, topdown, insert, findBest and chiSq.

Examples

# NOT RUN {
#----Calculating cacc value (Tsai, Lee, and Yang (2008))
a=c(3,0,3,0,6,0,0,3,0)
m=matrix(a,ncol=3,byrow=TRUE)
cacc(m)
# }