A kNN method that uses a non-natural evolutionary algorithm for component selection

Abstract

This paper details an evolutionary algorithm that forms a new population by combining genes
of three members of the current population. The first member is the best member of the
population, the second one is the current member to be replaced and the third one is a member
chosen randomly from the current population. We used this algorithm for component selection
of a kNN (k Nearest Neighbor) method for breast cancer prognosis. Results with the UCI
prognosis data set show that we can find components that help improve the accuracy of kNN
by almost 3%, raising it above 79%.

Keywords: kNN; classification; evolutionary algorithm; breast cancer, prognosis.