| cacc {discretization} | R Documentation |
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 |
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.
Value
val |
numeric of cacc value |
Author(s)
HyunJi Kim polaris7867@gmail.com
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
#----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)