Search Results
| 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 ridge-regression
Search options not deleted
user 240615
A regularization method for regression models that shrinks coefficients towards zero.
3
votes
0
answers
349
views
Why is it much quicker to compute ridge regression than regular linear regression? [duplicate]
By my understanding, for a matrix with n samples and p features:
Ridge regression using cholesky takes O(p^3) time
Ordinary linear regression takes O(p^3) time
Singular value decomposition if u, v a …
- 105
3
votes
1
answer
2k
views
Why is computing ridge regression with a Cholesky decomposition much quicker than using SVD?
By my understanding, for a matrix with n samples and p features:
Ridge regression using Cholesky decomposition takes O(p^3) time
Ridge regression using SVD takes O(p^3) time
Computing SVD when only …
- 105