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 maximum-likelihood
Search options not deleted
user 217348
a method of estimating parameters of a statistical model by choosing the parameter value that optimizes the probability of observing the given sample.
2
votes
1
answer
319
views
Soft classification after Fisher LDA with MLE
EDIT: any help is appreciated!
I am using Fisher's LDA for an image classification application. Let's say I have labeled data of 20 [100x100]px face images per person with a total of 100 persons, ev …
- 81
2
votes
Accepted
Soft classification after Fisher LDA with MLE
Fisher's LDA version maximizes a class-separability criterion, The ratio of the within class scatter to between class scatter. Where samples from the same class should be clustered tight together, and …
- 81