πŸ› οΈ
PySR tool by astroautomata
⭐ 63.9
πŸ› οΈ
Tool

PySR

by astroautomata astroautomata/pysr
Free2AITools Nexus Index
63.9
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 59
P: Popularity 64
R: Recency 100
Q: Quality 70
Tech Context
Vital Performance —
Source β†’
Python Lang
Open Source 3.8K Stars
Alpha Reliability
Tool Information Summary
Entity Passport
Registry ID astroautomata/pysr
License Apache-2.0
Provider github
πŸ“œ

Cite this tool

Academic & Research Attribution

BibTeX 
@misc{gh_tool_astroautomata_pysr,
  author = {astroautomata},
  title = {PySR Tool},
  year = {2020},
  howpublished = {\url{https://github.com/astroautomata/PySR}},
  note = {Accessed via Free2AITools.}
}
APA Style
astroautomata. (2020). PySR [Tool]. Free2AITools. https://github.com/astroautomata/PySR

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ™ GitHub Clone
git clone https://github.com/astroautomata/PySR
🐍 PIP Install
pip install pysr

βš–οΈ Free2AITools Nexus Index V2.0

Methodology How FNI works
Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 59
Popularity (P) 64
Recency (R) 100
Quality (Q) 70

πŸ’¬ Index Insight

FNI V2.0 for PySR: Authority (A:59), Popularity (P:64), Recency (R:100), Quality (Q:70). Semantic (S) is a query-time baseline scored live at search.

Free2AITools Nexus Index

Data Sources / Provenance

HuggingFace API GitHub Metadata Arxiv Citation DB Methodology
Open data Updated: Live data

πŸ“‹ Specs

Language
Python
License
Apache-2.0
Version
β€”
Explore Source Node
CODE

πŸ”Œ Usage & Integration

Quick Start

pip install pysr

Technical Documentation

PySR
Symbolic Regression in Python and Julia
Docs  Γ—  Examples  Γ—  API  Γ—  Forum  Γ—  Agents
PyPI conda-forge arXiv

bash 
pip install pysr

If you find PySR useful, please cite the paper arXiv:2305.01582. If you've finished a project with PySR, please submit a PR to showcase your work on the research showcase page!

Contents:

Why PySR?

PySR is an open-source tool for Symbolic Regression: a machine learning task where the goal is to find an interpretable symbolic expression that optimizes some objective.

Over a period of several years, PySR has been engineered from the ground up to be (1) as high-performance as possible, (2) as configurable as possible, and (3) easy to use. PySR is developed alongside the Julia library SymbolicRegression.jl, which forms the powerful search engine of PySR. The details of these algorithms are described in the PySR paper.

Symbolic regression works best on low-dimensional datasets, bu

Social Proof

GitHub Repository
3.8KStars
354Forks
Repo Issues
πŸ™ Data Source: GitHub β†—
πŸ”„ Updated daily

Source summary: Based on GitHub metadata. Not a recommendation.

πŸ“Š FNI Methodology πŸ“š Knowledge Baseℹ️ Verify with original source

πŸ›‘οΈ Tool Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

πŸ†” Identity & Source

id
gh-tool--astroautomata--pysr
slug
astroautomata--pysr
source
github
author
astroautomata
license
Apache-2.0
tags
symbolic-regression, machine-learning, python, julia, genetic-algorithm, automl, interpretable-ml, data-science, explainable-ai, scikit-learn, symbolic, algorithm, distributed-systems, evolutionary-algorithms, equation-discovery

βš™οΈ Technical Specs

pipeline tag
other

πŸ“Š Engagement & Metrics

downloads
0
stars
3,800
forks
354
github stars
3,800

Data indexed from public sources. Updated daily.