# symbolic-regression-with-genetic-programming > 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 Latest version **1.0.1** (published 2024-05-05) · ISC license · 0 weekly downloads ## Install ```sh npm install symbolic-regression-with-genetic-programming pnpm add symbolic-regression-with-genetic-programming yarn add symbolic-regression-with-genetic-programming bun add symbolic-regression-with-genetic-programming ``` ## Health **Score 15/100 (F)** — status: abandoned. Positive: no vulnerabilities. Warnings: low downloads; no types; no esm support. Negative: abandoned; low maintenance score. ## Facts | | | |---|---| | Version | 1.0.1 | | Published | 2024-05-05 | | First published | 2024-03-02 | | Weekly downloads | 0 | | License | ISC | | TypeScript types | none | | Module format | CommonJS | | Dependencies | 45 | | Unpacked size | 3.7 KB | | Known vulnerabilities | 0 | | Install scripts | no | | GitHub stars | 0 | | Maintainers | martinezmorris | ## Links - npm: https://www.npmjs.com/package/symbolic-regression-with-genetic-programming - Repository: https://github.com/isauo/Symbolic-Regression-with-Genetic-Programming - Homepage: https://github.com/isauo/Symbolic-Regression-with-Genetic-Programming#readme - Issues: https://github.com/isauo/Symbolic-Regression-with-Genetic-Programming/issues - npm.io page: https://npm.io/package/symbolic-regression-with-genetic-programming ## Dependencies (45) - [numpy](https://npm.io/package/numpy.md) ^1.21.3 - [dark-maze](https://npm.io/package/dark-maze.md) 1.0.0 - [neonninja](https://npm.io/package/neonninja.md) 1.0.0 - [aihua-game](https://npm.io/package/aihua-game.md) 1.0.3 - [datadynamo](https://npm.io/package/datadynamo.md) 1.0.0 - [matplotlib](https://npm.io/package/matplotlib.md) ^3.4.3 - [neon-blitz](https://npm.io/package/neon-blitz.md) 1.0.0 - [pixelpanic](https://npm.io/package/pixelpanic.md) 1.0.1 - [digit-merge](https://npm.io/package/digit-merge.md) 1.0.0 - [pixelpuzzle](https://npm.io/package/pixelpuzzle.md) 1.0.0 - [realm-cards](https://npm.io/package/realm-cards.md) 1.0.1 - [starsmasher](https://npm.io/package/starsmasher.md) 1.0.0 - [cipherscribe](https://npm.io/package/cipherscribe.md) 1.0.0 - [dark-journey](https://npm.io/package/dark-journey.md) 1.0.1 - [gravityglide](https://npm.io/package/gravityglide.md) 1.0.1 - [scikit-learn](https://npm.io/package/scikit-learn.md) ^0.24.2 - [virtualvoyage](https://npm.io/package/virtualvoyage.md) 1.0.0 - [adventurequest](https://npm.io/package/adventurequest.md) 1.0.0 - [cosmicconquest](https://npm.io/package/cosmicconquest.md) 1.0.0 - [cryptocompanion](https://npm.io/package/cryptocompanion.md) 1.0.1 - [serpentine-quest](https://npm.io/package/serpentine-quest.md) 1.0.0 - [tictactoe-api-feng](https://npm.io/package/tictactoe-api-feng.md) 1.0.4 - [ruby-task-scheduler](https://npm.io/package/ruby-task-scheduler.md) 1.0.2 - [space-adventure-game](https://npm.io/package/space-adventure-game.md) 1.0.0 - [automated-file-backup](https://npm.io/package/automated-file-backup.md) 1.0.0 - [random-famous-library1](https://npm.io/package/random-famous-library1.md) ^1.0.0 - [random-famous-library2](https://npm.io/package/random-famous-library2.md) ^2.0.0 - [tictactoe-api-penglang](https://npm.io/package/tictactoe-api-penglang.md) 1.0.7 - [automated-email-sending](https://npm.io/package/automated-email-sending.md) 1.0.0 - [fantasy-quest-adventure](https://npm.io/package/fantasy-quest-adventure.md) 1.0.0 - [file-encryption-program](https://npm.io/package/file-encryption-program.md) 1.0.1 - [automated-database-backup](https://npm.io/package/automated-database-backup.md) 1.0.0 - [automated-image-processing](https://npm.io/package/automated-image-processing.md) 1.0.0 - [simple-calculator-program9](https://npm.io/package/simple-calculator-program9.md) 1.0.1 - [javascript-quiz-application](https://npm.io/package/javascript-quiz-application.md) 1.0.1 - [python-data-analysis-script](https://npm.io/package/python-data-analysis-script.md) 1.0.1 - [java-command-line-calculator](https://npm.io/package/java-command-line-calculator.md) 1.0.1 - [java-file-management-utility](https://npm.io/package/java-file-management-utility.md) 1.0.2 - [automated-data-transformation](https://npm.io/package/automated-data-transformation.md) 1.0.0 - [python-image-processing-script](https://npm.io/package/python-image-processing-script.md) 1.0.2 - [javascript-todo-list-application](https://npm.io/package/javascript-todo-list-application.md) 1.0.2 - [hierarchical-clustering-algorithm](https://npm.io/package/hierarchical-clustering-algorithm.md) 1.0.0 - [quantum-error-correction-simulator](https://npm.io/package/quantum-error-correction-simulator.md) 1.0.0 - [genetic-algorithm-for-feature-selection](https://npm.io/package/genetic-algorithm-for-feature-selection.md) 1.0.0 - [reinforcement-learning-with-deep-q-networks](https://npm.io/package/reinforcement-learning-with-deep-q-networks.md) ^1.0.0 ## Recent versions - 1.0.1 (latest) — 2024-05-05 - 1.0.0 — 2024-03-02 ## README # Symbolic Regression with Genetic Programming 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. ## Usage: 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. ## Features: - 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. ## Requirements: - Python 3.x - NumPy - SymPy --- _Source: https://npm.io/package/symbolic-regression-with-genetic-programming · Machine-readable twin of the npm.io package page. Health data is recomputed on every publish._