https://github.com/sadit/searchmodels.jl

Searching configurations in abstract spaces using stochastic search methods
https://github.com/sadit/searchmodels.jl

Last synced: 3 months ago
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Searching configurations in abstract spaces using stochastic search methods

• Host: GitHub
• URL: https://github.com/sadit/searchmodels.jl
• Owner: sadit
• License: mit
• Created: 2021-02-16T16:57:58.000Z (over 4 years ago)
• Default Branch: main
• Last Pushed: 2024-11-18T13:57:51.000Z (6 months ago)
• Last Synced: 2025-02-22T22:21:39.594Z (3 months ago)
• Language: Julia
• Size: 295 KB
• Stars: 1
• Watchers: 2
• Forks: 0
• Open Issues: 3
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# SearchModels

[![Dev](https://img.shields.io/badge/docs-dev-blue.svg)](https://sadit.github.io/SearchModels.jl/dev)

[![Build Status](https://github.com/sadit/SearchModels.jl/workflows/CI/badge.svg)](https://github.com/sadit/SearchModels.jl/actions)

[![Coverage](https://codecov.io/gh/sadit/SearchModels.jl/branch/main/graph/badge.svg)](https://codecov.io/gh/sadit/SearchModels.jl)

Provides a generic tool for minimizing model errors using stochastic search, which is often used whenever the problem has no concept of derivative. This kind of problems rely on large exploration of combinatorial spaces based on error function.

SearchModels rely on basic exploration functions that can be specified for many applications.

Due to its generic specification, other kind of optimization problems can be also solved, however, it could be easier and better to use other approaches, like `Optim.jl`.

## Installing

```julia

] add SearchModels

```