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 |
Refers generally to statistical procedures that utilize the logistic function, most commonly various forms of logistic regression
0
votes
Flexible version of logistic regression
If you want a classification technique that is insensitive to the relative proportion of examples from different classes, Support Vector Machines have that property as do decision trees.
5
votes
1
answer
249
views
Constrain decision boundary to fall on grid lines in multiple class logistic regression
I would like to use multiple class logistic regression to learn the decision boundaries separating the different classes (denoted by color) in the image below. … Kernel logistic regression with a RBF kernel seems like a good choice, but I would like the decision boundary, when projected back to the 2-d space, to fall along the white grid lines. …
20
votes
2
answers
13k
views
Logit with ordinal independent variables
In a logit model, is there a smarter way to determine the effect of an independent ordinal variable than to use dummy variables for each level?
8
votes
Independent variables in ordinal logistic regression
Let's think about regular linear regression, and to make it concrete, let's say we are trying to predict height of people. When you regress heights against just an intercept term and no predictors, th …