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 regression
Search options not deleted
user 140965
Techniques for analyzing the relationship between one (or more) "dependent" variables and "independent" variables.
4
votes
Accepted
Derivation of AdaBoost.R2 algorithm
The choice to use the weighted median appears to be arbitrary. According to this "the
idea of using the weighted median as the final regressor is not new. Freund [6] briefly mentions it and proves a …
- 1,367
0
votes
Is there any Generative Model which can be used for Regression problems?
Managed to find that GMMs are considered generative, and it is possible to do regression with them, though this is so uncommon that sklearn doesn't have it.
There must be other examples. …
- 1,367
4
votes
3
answers
4k
views
Is there any Generative Model which can be used for Regression problems?
In regression problems we generally just try to find that relationship $x \rightarrow y$. … Are there learning models that do that sort of probabilistic reasoning for regression problems? Are there any that could be considered Generative which can handle the regression case? …
- 1,367
5
votes
2
answers
4k
views
How to handle dependent, multidimensional output in machine learning
I have some data where X is n x p and Y is n x d, where d = 36. To recreate it I am currently training 36 independent models to take X and recreate Y one column at a time. It works okay, but it strike …
- 1,367
5
votes
Accepted
How to handle dependent, multidimensional output in machine learning
Like statistical models, Multi-Output Support Vector Regression "mainly rel[ies] on the idea of embedding the output space. … In Algebra II we learned about basic regression, coming up with a function to map a single input to a single output. …
- 1,367