Machine Learning Methods: Classification without negative examples – EFavDB

Here, we discuss some methods for carrying out classification when only positive examples are available. The latter half of our discussion borrows heavily from W.S. Lee and B. Liu, Proc. Follow @efavdb Follow us on twitter for new submission alerts! Logistic regression is a commonly used tool for estimating the level sets of a Boolean function y on a set of feature vectors \textbf{F}: In a sense, you can think of it as a method for playing the game "Battleship" on whatever data set you're interested in. Consider now a situation where all training examples given are positive -- i.e., no negative examples are available.