AUTHOR(S): Ivaylo Penev, Milena Karova, Mariana Todorova

TITLE Exploration of the K Parameter in HandWritten Digit Recognition by KNearest Neighbor Algorithm 
KEYWORDS machine learning, nearest neighbors, kNN, handwritten digits, recognition, classification 
ABSTRACT The paper presents application of the knearest neighbor algorithm (kNN) for recognition of handwritten digits from 0 to 9. The emphasis is on the choice of the number of the nearest neighbors (the k parameter), which has significant impact on the algorithm performance. The main steps of the algorithm are described. The function for distance calculation and the method for choosing a class of the recognized digit are explained. Experimental results are presented. According to the results recommendations for the choice of k are summarized. The aim is increasing the performance of the kNN algorithm for the handwritten digit recognition problem, regarding two criteria – percent of the correctly recognized input data and time for recognition. 
Cite this paper Ivaylo Penev, Milena Karova, Mariana Todorova. (2016) Exploration of the K Parameter in HandWritten Digit Recognition by KNearest Neighbor Algorithm. International Journal of Control Systems and Robotics, 1, 158161 