Genetic Algorithms vs Polynomial Regression

Genetic algorithms are one of the search and optimisation methods. The aim of optimisation is to increase efficiency in reaching a certain optimal value. Genetic algorithms are based on the mechanisms of natural selection and heredity. The basic genetic algorithm is built from three operations: reproduction, crossing, and mutation. Genetic algorithms operate on populations of coding sequences and use random selection rules to search for the global optimal value. However, these random rules are defined to give the appropriate direction of the search (through various selection mechanisms or scaling of fitness functions). This basic procedure is enhanced by certain genetic manipulations, such as those seen in nature. They include the mechanisms of dominance, diploidy, inversion, and other reconfiguration mechanisms that occur at the chromosome level. Users can design textual or graphical scaling patterns for the fitness function and then use them in simulations. The application also provides a preliminary analysis of statistical data concerning the distribution of the fitness function in the population. The program allows the user to compare non-random procedures (e.g. scaling of fitness functions) by using the same pseudorandom sequence (for procedures requiring randomization, such as selection, etc.) in successive simulations. In order to better visualize the genetic processes taking place during the simulation, some of them are presented to the user using animations. Additionally, some of the data obtained from simulations can be saved and shared.

Polynomial Regression is your calculator and, more importantly, learning tool. You will be able to: * Construct polynomials of up to 20 degrees from either real or complex roots. * Interpolate polynomials from points by Lagrange, Newton or Vandermonde methods and Quadratic or Cubic splines. * Perform Least Squares approximation by orthogonal projection, with or without QR factorization, or partial derivatives. * Learn about each of the algorithms with derivations, proofs, step by step demonstrations, and visual tools. * Have an option to enter data by either typing or tapping on XY plane, and save data sets between program runs.