Displaying 5 results from an estimated 5 matches for "cv_model".
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2023 Oct 24
1
running crossvalidation many times MSE for Lasso regression
...y=c(2,6,5,4,6,7,8,10,11,2,3,1,3,5,4,6,5,3.4,5.6,-2.4,-5.4,5,3,6,5,-3,-5,3,2,-1,-8,5,8,6,9,4,5,-3,-7,-9,-9,8,7,1,2)
>> ? ? ? >> >> T=data.frame(y,x1,x2)
>> ? ? ? >> >>
>> ? ? ? >> >> z=matrix(c(x1,x2), ncol=2)
>> ? ? ? >> >> cv_model=glmnet(z,y,alpha=1)
>> ? ? ? >> >> best_lambda=cv_model$lambda.min
>> ? ? ? >> >> best_lambda
>> ? ? ? >> >>
>> ? ? ? >> >>
>> ? ? ? >> >> # Create a list to store the results
>> ? ? ? >> >...
2023 Oct 23
1
running crossvalidation many times MSE for Lasso regression
...>
>? ? ? >> y=c(2,6,5,4,6,7,8,10,11,2,3,1,3,5,4,6,5,3.4,5.6,-2.4,-5.4,5,3,6,5,-3,-5,3,2,-1,-8,5,8,6,9,4,5,-3,-7,-9,-9,8,7,1,2)
>? ? ? >> >> T=data.frame(y,x1,x2)
>? ? ? >> >>
>? ? ? >> >> z=matrix(c(x1,x2), ncol=2)
>? ? ? >> >> cv_model=glmnet(z,y,alpha=1)
>? ? ? >> >> best_lambda=cv_model$lambda.min
>? ? ? >> >> best_lambda
>? ? ? >> >>
>? ? ? >> >>
>? ? ? >> >> # Create a list to store the results
>? ? ? >> >> lst<-list()
>? ? ? >&...
2023 Oct 22
1
running crossvalidation many times MSE for Lasso regression
...,154,21,34,26,56,78,99,83,46,58,91)
x2=c(1,3,2,4,5,6,7,3,8,9,10,11,12,1,3,4,2,3,4,5,4,6,8,7,9,4,3,6,7,9,8,4,7,6,1,3,2,5,6,8,7,1,1,2,9)
y=c(2,6,5,4,6,7,8,10,11,2,3,1,3,5,4,6,5,3.4,5.6,-2.4,-5.4,5,3,6,5,-3,-5,3,2,-1,-8,5,8,6,9,4,5,-3,-7,-9,-9,8,7,1,2)
T=data.frame(y,x1,x2)
z=matrix(c(x1,x2), ncol=2)
cv_model=glmnet(z,y,alpha=1)
best_lambda=cv_model$lambda.min
best_lambda
?
?
# Create a list to store the results
lst<-list()
?
# This statement does the repetitions (looping)
for(i in 1?:1000) {
?
n=45
?
p=0.667
?
sam=sample(1?:n,floor(p*n),replace=FALSE)
?
Training =T [sam,]
Testing = T [-sam,]
?
test1...
2023 Oct 22
2
running crossvalidation many times MSE for Lasso regression
...58,91)
> x2=c(1,3,2,4,5,6,7,3,8,9,10,11,12,1,3,4,2,3,4,5,4,6,8,7,9,4,3,6,7,9,8,4,7,6,1,3,2,5,6,8,7,1,1,2,9)
> y=c(2,6,5,4,6,7,8,10,11,2,3,1,3,5,4,6,5,3.4,5.6,-2.4,-5.4,5,3,6,5,-3,-5,3,2,-1,-8,5,8,6,9,4,5,-3,-7,-9,-9,8,7,1,2)
> T=data.frame(y,x1,x2)
>
> z=matrix(c(x1,x2), ncol=2)
> cv_model=glmnet(z,y,alpha=1)
> best_lambda=cv_model$lambda.min
> best_lambda
>
>
> # Create a list to store the results
> lst<-list()
>
> # This statement does the repetitions (looping)
> for(i in 1 :1000) {
>
> n=45
>
> p=0.667
>
> sam=sample(1 :n,floor(p*n),...
2023 Oct 23
2
running crossvalidation many times MSE for Lasso regression
...>
> >> y=c(2,6,5,4,6,7,8,10,11,2,3,1,3,5,4,6,5,3.4,5.6,-2.4,-5.4,5,3,6,5,-3,-5,3,2,-1,-8,5,8,6,9,4,5,-3,-7,-9,-9,8,7,1,2)
> >> >> T=data.frame(y,x1,x2)
> >> >>
> >> >> z=matrix(c(x1,x2), ncol=2)
> >> >> cv_model=glmnet(z,y,alpha=1)
> >> >> best_lambda=cv_model$lambda.min
> >> >> best_lambda
> >> >>
> >> >>
> >> >> # Create a list to store the results
> >> >> lst<-list()
> >&...