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
Sections title:apples
body:"apples oranges"
URL url:"*.example.com"
Favorites infavorites:mine
infavorites:1234
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 user 1119

Statistical classification is the problem of identifying the sub-population to which new observations belong, where the identity of the sub-population is unknown, on the basis of a training set of data containing observations whose sub-population is known. Therefore these classifications will show a variable behavior which can be studied by statistics.

0
votes
Usually the term for this is Gaussian Mixture Modeling, which along with kMeans is one of the most popular and widely implemented clustering algorithms out there. Each Gaussian has a mean and varianc …
answered Jul 15 '14 by Joe
0
votes
It's problematic that you're not getting full support. One way to solve this is to produce: A model to decide whether or not results are shown - $P(shown)$, and then Another model, $P(relevant|show …
answered Jun 25 '14 by Joe
6
votes
SMOTE isn't really about changing f-measure or accuracy... it's about the trade-off between precision vs. recall. By using SMOTE you can increase recall at the cost of precision, if that's something …
answered May 13 '14 by Joe
28
votes
Popular right now are randomForest and gbm (called MART or Gradient Boosting in machine learning literature), rpart for simple trees. Also popular is bayesglm, which uses MAP with priors for regulari …
answered Aug 31 '10 by Joe
2
votes
Something very similar is Logistic regression with a Radial Basis Function (sometimes called Gaussian) kernel (http://en.wikipedia.org/wiki/Radial_basis_function_kernel), with all weights constrained …
answered Apr 21 '14 by Joe