Hi,
I modified dlda{supclust} so that the original example in ?dlda gives
the following output:
> set.seed(342)
> xlearn <- matrix(rnorm(200), nrow = 20, ncol = 10)
>
> ## Generating random test data: 8 observations and 10 variables(clusters)
> xtest <- matrix(rnorm(80), nrow = 8, ncol = 10)
>
Hi,
I am using dlda algorithm from supclust package and I am wondering if
the output can be a continuous probability instead of discrete class
label (zero or one) since it puts some restriction on convariance
matrix, compared with lda, while the latter can.
thanks,
--
Weiwei Shi, Ph.D
Research
