Description Usage Arguments Value
To obtain SODC components and other relevant predictions in SODC method.
1 | my.lasso.classify(data, c, lambda1, lambda2, tol = 10^(-10), iter.max = 50)
|
data |
A numberic dataset matrix. |
c |
An integer scalar with the desired number of groups. |
lambda1 |
L1 penalty parameter, if lambda1=-1, then odc.clust choose the optimal lambda2 automatically given lambda2.idx. Otherwise perfoms SODC clustering using given lambda1. |
lambda2 |
L2 penalty parameter, if lambda2=-1, then odc.clust choose the optimal lambda2 automatically given lambda2.idx. Otherwise perfoms ODC clustering using given lambda2. |
tol |
A tolerance value indicating the degree of prediction error of W. |
iter.max |
the maximum number of iterations allowed. |
Z |
The SODC component.It is an n by k-1 matrix where n is the number of observations. |
varset |
An array indicating the selected varialbes index numbers. |
what |
Predicted W using SODC method. |
nvarselected |
The number of selected varialbes by SODC.The smaller the value, the sparser. |
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