Symbolic Regression with Genetic Programming is a Python class that performs symbolic regression using genetic programming techniques. It allows users to discover mathematical expressions that best fit the given data, without making any assumptions about the form of the underlying function.

1. Initialize the GeneticProgramming object with the desired parameters.
2. Fit the model to the data using the fit method.
3. Predict target values for new data points using the predict method.

• Automatically discovers mathematical expressions from data using genetic programming.
• Supports customization of population size, number of generations, and other parameters.
• Provides interpretable solutions in the form of symbolic expressions.

• Python 3.x
• NumPy
• SymPy