Hello,
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 coefficient paths for the fit.
I wanted to know how to interpret the above figure and what exactly does a coefficient 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”)
which generates:
How do I interpret this graph??
Can somebody please help me with these questions,I am stuck for a long time on these!!