Hi All,
I have been trying to use glmnet package to do LASSO linear regression. my x
data is a matrix n_row by n_col and y is a vector of size n_row corresponding
to the vector data. The number of n_col is much more larger than the number of
n_row. I do the following:
fits = glmnet(x, y, family="multinomial")I have been following this
article: http://cran.r-project.org/web/packages/glmnet/glmnet.pdfpage 8, but
there are some unclear parts that I dont understand. The lambda variable only
returns 100 and I exactly dont know what lambda represents. So, basically I
would like to know how to get the coefficients weights and what exactly lambda
is? how I can see the difference between predicted values and observed values?
If there is a sample code that helps me to understand how to use these, that
would be great.
Thanks a lot,Andra
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