The Influence of Polynomial Order in Logistic Regression on Decision Boundary
Xing Yu Wan · IOP Conference Series Earth and Environmental Science · 2019
Abstract In machine learning problems, polynomial logistic regression algorithms are often used to classify data. Compared to linear regression, polynomial regression can not only deal with linear problems, but also deal with nonlinear problems. In the polynomial logistic regression algorithm, the polynomial order has a certain influence on the classification effect. This paper studies the influence of the polynomial order on the binary decision boundary in binary classification problem. By choosing different parameter values, an approximate optimal solution can be found.