Skip to main content
Search type Search syntax
Tags [tag]
Exact "words here"
Author user:1234
user:me (yours)
Score score:3 (3+)
score:0 (none)
Answers answers:3 (3+)
answers:0 (none)
isaccepted:yes
hasaccepted:no
inquestion:1234
Views views:250
Code code:"if (foo != bar)"
Sections title:apples
body:"apples oranges"
URL url:"*.example.com"
Saves in:saves
Status closed:yes
duplicate:no
migrated:no
wiki:no
Types is:question
is:answer
Exclude -[tag]
-apples
For more details on advanced search visit our help page
Results tagged with
Search options not deleted user 100345

A regularization method for regression models that shrinks coefficients towards zero, making some of them equal to zero. Thus lasso performs feature selection.

3 votes
0 answers
196 views

Why does lasso return unstable features when using the same data?

It is a very noisy data (market and economic data) To my best knowledge, lasso returns same features for the same data set. However, I don't observe this through my runs. … return features print('Performing LASSO feature selection...') X_train = self. …
mlee_jordan's user avatar
3 votes
3 answers
1k views

LASSO or random forest (RF) to use for variable selection when having highly correlated feat...

I know that LASSO can be used to shrink feature set since it can set coefficients to zero depending on the penalization weight. … Considering that LASSO gives stable results for the same data-set, first I am planning to use it to shrink the feature set (from 1000 to 100) and then apply RF for the variable importance. …
mlee_jordan's user avatar