The Application of Support Vector Machine with Elastic Net Regularizationin in Classification of Wheat Seeds

Abstract

Machine Learning is playing a big part in data analysis. Aiming at the problem of wheat seed classification, Seed data from UCI Machine Learning Repository is used as experimental data in this paper, firstly Support Vector Machine (SVM) algorithm is used to classify and predict the test set samples of wheat seed data sets. Secondly, Support Vector Machine (SVM) algorithm with Lasso and elastic net regularization is used to classify and predict wheat seed. The experimental results show that the SVM-Elastic Net model has high classification accuracy.