Learn how to apply the Wolfram System's recent advances in disciplined convex programming to a multi-objective optimization problem in this 30-minute video. Explore the process of finding a cubic spline function with small data distance and curvature while incorporating positivity, monotonicity, and convexity constraints expressed as norm cone constraints. Dive into topics such as datafitting, spline functions, non-negativity, higher degree polynomials, positive polynomials, and automotive applications. Gain valuable insights into taming your data through constrained spline regression techniques.
Tame Your Data - Constrained Spline Regression in the Wolfram System
Overview
Syllabus
Introduction
About Continental
Background
Datafitting
Spline Function
Non Negativity
Higher Degree Polinomial
Positive Polinomial
Automotive Application
Summary
Taught by
Wolfram
