Research on GA-KNN Image Classification Algorithm

This paper studies KNN algorithm and analyzes the factors that affect the accuracy of image classification. Then the algorithm is improved by optimizing the selection strategy of K value in traditional KNN model using the characteristics of genetic algorithm, which is survival of the fittest and survival of the fittest. The Fasion-MNIST dataset is selected to extract the gray pixel value of the image. KNN algorithm model and GA-KNN algorithm model have been trained, and the classification accuracy of the latter is improved by nearly 10%, making the image classification effect better.