1.While trying to learn about regularization techniques I am trying to use the Lasso fitting algorithm via:
library(faraway) data(prostate) attach(prostate) # Set sample: set.seed(321); i.train <- sample(1:97, 67) x.train <- prostate[i.train, 1:8]; y.train <- prostate[i.train, 9] x.test <- prostate[-i.train, 1:8]; y.test <- prostate[-i.train, 9] library(lars) fit.lasso <- lars(as.matrix(x.train), y.train, type="lasso") plot(fit.lasso, breaks=F, xvar="norm")
The last command generates a plot:
In the resource that I am using it is given that the last command plots the co-efficient paths for the fit.
I wanted to know how to interpret the above figure and what exactly does a co-efficient path mean?
Next to select the optimal value of the coefficient vector a along these paths,we use cross validation as:
cv.lasso <- cv.lars(as.matrix(x.train), y.train, type=“lasso”)
How do I interpret this graph??
Can somebody please help me with these questions,I am stuck for a long time on these!!