CSE251A Project 1: K-Means Clustering based Prototype Selection for Nearest Neighbor

In the report, we discuss our attempt to choose a better prototype for nearest neighbor other than random selection.We present a KMeans based prototype selection method that clearly outperforms the naive random selection in all our experiments.

荣懿
荣懿
计算机科学&工程

My research interests include Machine Learning, Compilers and PL Design