my.lasso.classify

data


An integer scalar with the desired number of groups.



L1 penalty parameter, if lambda1=-1, then odc.clust choose the optimal lambda2 automatically given lambda2.idx. Otherwise perfoms SODC clustering using given lambda1. 


lambda1


L2 penalty parameter, if lambda2=-1, then odc.clust choose the optimal lambda2 automatically given lambda2.idx. Otherwise perfoms ODC clustering using given lambda2. 


lambda2


A tolerance value indicating the degree of prediction error of W.



the maximum number of iterations allowed.<p></p><p></p>

iter.max


To obtain SODC components and other relevant predictions in SODC method.


 ~kwd1 

 ~kwd2 

To implement two clustering methods, ODC and SODC, for
clustering datasets using optimal scoring, can also be used as
an dimension reduction tool.

my.lasso.classify: Sparse Optimal Discriminant Clustering

Description

Usage

Arguments

Value