This repository implements a Genetic Algorithm (GA) designed to fit polynomials to various datasets. The project simulates evolution to find optimal polynomial coefficients that minimize the error between the predicted and actual data points.
- Polynomial Fitting: Supports fitting constants, quadratic, cubic, and other polynomials.
- Customizable Scenarios: Easy-to-define functions for specific use cases.
- Genetic Operations: Includes selection, crossover, mutation, and elitism.
- Visualization: Plots fitness over generations for performance tracking.
- Flexible Parameters: Configurable population size, mutation rate, and number of generations.
- Python 3.x
- Required libraries:
numpymatplotlib