Skip to main content

Equation Tree

The Equation Tree package is an equation toolbox with symbolic regression in mind. It represents expressions as incomplete binary trees and has various features tailored towards testing symbolic regression algorithms or training models. The main features are:

  • Equation sampling (including priors)
  • Feature Extraction from equation distributions
  • Distance metrics between equations

Getting Started

Check out the documentation at https://autoresearch.github.io/equation-tree.

About

This project is in active development by the Autonomous Empirical Research Group (package developers: Ioana Marinescu and Younes Strittmatter, PI: Sebastian Musslick. This research program is supported by Schmidt Science Fellows, in partnership with the Rhodes Trust, as well as the Carney BRAINSTORM program at Brown University.

Metadata

Release files for equation-tree 0.0.33

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for equation-tree 0.0.33
File Size Uploaded
equation_tree-0.0.33.tar.gz 805.0 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for equation-tree 0.0.33
File Interpreter ABI Platform
equation_tree-0.0.33-py3-none-any.whl Python 3 none any Details

Total release size: 871.2 kB

Release files / equation_tree-0.0.33.tar.gz

Download URL equation_tree-0.0.33.tar.gz
Size 805.0 kB
Tags Source
SHA-256 checksum
How to use checksums
bac330eacfc8529e5a7d1848381af006d9266e9696fc88ef242effd060487a17
BLAKE2b-256 checksum
How to use checksums
f9a303f6532d532e824f6ef1345800475df83c82e5232432a7a74994cdb1a762
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/5.0.0 CPython/3.9.18

Release files / equation_tree-0.0.33-py3-none-any.whl

Download URL equation_tree-0.0.33-py3-none-any.whl
Size 66.2 kB
Tags Python 3
SHA-256 checksum
How to use checksums
451b64314eb2adc92272c6e042968d8cc063661f943ef629f14a1b1b3d5135d9
BLAKE2b-256 checksum
How to use checksums
50880e2d89695dc256ce36b3ca4010e67244fc9f2a85a1ddf7fe3050dfda65ab
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/5.0.0 CPython/3.9.18
Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page