The results can be seen in the graph below, where the blue line is my cramer fit, and the red dashed line is numpy's polyfit curve. We're actually not that far off, but I think there is abetter way to ...

I implemented a linear regression model and a polynomial regression model with a single input variable using gradient descent algorithm. My polynomial regression model can be used for any number of ...

In what follows, we want to review and discuss possibilities of a parameterized view on bypassing established complexity barriers for polynomial-time solvable problems. More specifically, we focus on ...

Abstract In this paper, an algebraic method which is based on the groebner bases theory is proposed to solve the polynomial functions conditional extreme. Firstly, we describe how to solve conditional ...

Understanding Concepts of Polynomial Equations: find the topic and its importance and types. Download or read complete content here.

Khachiyan, and recently Karmarkar, gave polynomial algorithms to solve the linear programming problem. These algorithms have a small theoretical drawback; namely, the number of arithmetic steps ...

This study focuses on minimizing the expectation of a polynomial cost function for linear systems with time-invariant stochastic parameters. These polynomial and time-invariant properties cause ...

Solving polynomials We solve polynomials algebraically in order to determine the roots - where a curve cuts the x -axis. A root of a polynomial function, f (x), is a value for x for which f (x) = 0.

Linear Algebraic Analogues of the Graph Isomorphism Problem and the Erdős-Rényi Model Abstract: A classical difficult isomorphism testing problem is to test isomorphism of p-groups of class 2 and ...