Kernelized Weighted-K Nearest Neighbors

Abstract

The objective of this work was to use kernelization inside in conjunction with the K - Neighbors method to observe how observations in different dimensional spaces would behave, and if better results could be obtained from kernelization. The paper presented good results summarized in poster form and oral presentation during the First Conference in Data Science and Statistics at the Federal University of Bahia.

Mateus Maia

Master’s Student in Statistics

My research interests include machine learning, statistical learning, ensemble methods and data-driven solutions to real world problems.