I am interested in a family of multivariate distributions that can be seen as a generalization of the multivariate normal distribution, insofar as they are defined by an expectation value $\vec \mu$ ...
I'm trying to determine a good model to use to predict multivariate count data given a row of multivariate normal as inputs. The training set is N*D and the response set is N*P, where N is the ...
I am seeking to augment random forest classification using Shannon-Weaver mutual information as a metaheuristic to partition candidate datasets. Specifically, I am trying to determine if such an ...
I applied SVM to perform the classification against several data sets. It turns out that the performance metric of recall is pretty bad for one data set. It has recall around 50% while other data sets ...
Can anybody point me to a survey paper on "Large $p$, Small $n$" results? I am interested in how this problem manifests itself in different research contexts, e.g. regression, classification, ...
Say I have a set of sample points generated by a multivariate normal distribution D whose parameters I don't know. I want to be able to measure the distance from an arbitrary point to the ...
What are the variable/feature selection that you prefer for binary classification when there are many more variables/feature than observations in the learning set? The aim here is to discuss what is ...