Research on Data Classification Perception Based on Artificial Bee Colony Algorithm
WANG Xiaojun
Abstract：The perception data classification is the training data examples of linear separability which is separated into two kinds of positive and negative hyperplane classification criterion which is the minimum classification error point,minimization of a loss function by using the gradient descent method,obtain the separating hyperplane.However,the hyperplane obtained by this iter-ation method is not unique,and has a good effect on the classification of training data.It may have poor classification effect on the test set data,that is,the generalization ability is not satisfactory.In this paper,the artificial bee colony algorithm is used to solve the data classification perceptron model,and a loss function suitable for bee colony algorithm is constructed,which improves the classification accuracy of the algorithm.
Keywords：data classification perceptionartificial bee colony algorithmseparation hyperplane
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( 866-869,915 )