Multi-variable regression methods using modified Chebyshev polynomials of class 2.

So far, many regression works have been implemented by using linear regression methods. Although more accurate predictions results could be obtained, polynomial regression is not used as much as compared to linear regression in real applications due to occurrence of coefficient explosion. To overcome this problem, two regression algorithms using Chebyshev polynomials of class 2 based on cascade regression and feature selection are proposed in this paper. In the experimental part, three separate experiments including function interpolation and real-case regression were conducted on three datasets to test the proposed algorithms. As shown by the experimental results, the proposed algorithms performed better than other regression methods in terms of both accuracy and processing time.