Hello!
I am trygng to study the normality of the residuals values of a model, but it gives me null values:
cv.lasso$residuals
NULL
cv.ridge$residuals
NULL
I know that when it happens it means at the model is not good.
Can anybody just see if it whar I did is right?
Thank you.
I tryed:
sapply(dat, function(x) sum(is.na(x)))
datOHE <- model.matrix(sex~.-1, dat)
head(datOHE)
train<-datOHE[1:317,]
test<-datOHE[318:nrow(datOHE),]
dim(train)
dim(test)
table(dat[1:317,]$sex)
table(dat[318:nrow(dat),]$sex)
##ridge
install.packages("MASS")
library(MASS)
library(glmnet)
X<-data.matrix(subset(train, select=-salary))
Y<-data.matrix(dat[1:317,]$salary)
str(X)
set.seed(42)
cv.ridge<-cv.glmnet(X, Y, family="gaussian", alpha=0, type.measure="mse")
plot(cv.ridge)
cv.ridge$lambda.min
min(cv.ridge$cvm)
coef(cv.ridge, s=cv.ridge$lambda.min)
predict.glmnet(cv.ridge$glmnet.fit, newx=X[1:2,], s=cv.ridge$lambda.min)
##Lasso
set.seed(42)
cv.lasso <- cv.glmnet(X, Y, family='gaussian', alpha=1, type.measure='mse')
plot(cv.lasso)
cv.lasso$lambda.min
min(cv.lasso$cvm)
predict.glmnet(cv.lasso$glmnet.fit, newx=X[1:2,], s=cv.lasso$lambda.min)
cv.lasso$residuals
cv.ridge$residuals
dput(dat):
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