Description Usage Arguments Value
To perform Sparse Optimal Discriminant Clustering
1 2 |
x |
A numberic dataset matrix. |
centers |
An integer scalar with the desired number of groups. |
l1 |
L1 penalty parameter. The larger lambda1, the sparser result. if l1==-1, will automatically select optimal lambda1. |
l2 |
L2 penalty parameter. if l2==-1, will automatically select optimal lambda2. |
cv.num |
The numbers of cross validation iteration for selecting tuning parameter lambda2. |
clus |
The clustering method applied on SODC component. |
boot.num |
The numbers of bootstrap iteration for selecting tuning parameter lambda1. |
l2.idx |
A sequence of index numbers from which one can get a sequence of lambda2 values by calculating 10^l2.idx. |
l1.idx |
A sequence of index numbers from which one can get a sequence of lambda1 values by calculating 10^l1.idx. |
cl |
An object of class "kmeans" or other class depending on the value of argument "clus" using SODC component. |
clvar |
An object of class "kmeans" or other class depending on the value of argument "clus" using SODC selected varialbes. |
opt.lambda1 |
optimal lambda1 selected. If l1!=-1, will return opt.lambda1=l1. |
opt.lambda2 |
optimal lambda2 selected. If l2!=-1, will return opt.lambda2=l2. |
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