An Optimal Solution Algorithm Based on k-nearest Neighbour Algorithm
ZHU Lizhi
Abstract：k-nearest neighbor algorithm,simulated annealing algorithm and particle swarm optimization(pso)algorithm are classified and the solving algorithm,the three algorithms are different and each algorithm has its own characteristics. Instance using the k-nearest neighbor algorithm,using the Euclidean distance formula to calculate the distance between the instance to find the op?timal solution,finally realizes the classification of the instance. In this paper,based on the characteristics of the k-nearest neighbor algorithm and the included Angle cosine similarity algorithm is put forward in the k-nearest neighbor classification algorithm in the application and calculation,so as to achieve the instance classification to find the optimal solution. The similarity algorithm in the search for a more optimal solution for application,and the included Angle cosine algorithm as the solution of the evaluation criterion which is the innovation of this article.
Keywords：similarityclusteringk-nearest neighbour algorithmparticle swarmincluded Angle cosine
Publication Date：2018-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 35-38,148 )