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Model-based framework for robust classification that jointly accounts for outliers, label noise and unobserved classes in the test set.
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Andrea Cappozzo HID
Latest commit 1120ac5 Jul 5, 2019

README.md

Lifecycle: experimental

raedda

Model-based framework for robust classification that jointly accounts for outliers, label noise and unobserved classes in the test set, employing a MVN mixture model with Parsimonious structure.

Installation

You can install the development version of raedda from github with:

devtools::install_github("AndreaCappozzo/raedda")
You can’t perform that action at this time.