https://github.com/d6y/oner_quantize

Qualization library based on 1R
https://github.com/d6y/oner_quantize

1r machine-learning oner quantization rule-based rust-lang

Last synced: about 1 month ago
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Qualization library based on 1R

• Host: GitHub
• URL: https://github.com/d6y/oner_quantize
• Owner: d6y
• License: mpl-2.0
• Created: 2019-10-07T13:22:25.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2020-04-13T16:44:51.000Z (over 4 years ago)
• Last Synced: 2024-11-21T22:49:17.839Z (about 2 months ago)
• Topics: 1r, machine-learning, oner, quantization, rule-based, rust-lang
• Language: Rust
• Homepage:
• Size: 67.4 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
![Rust](https://github.com/d6y/oner_quantize/workflows/Rust/badge.svg)

# 1R quantization implementation in Rust

Quantization takes numeric data and turns it into a discrete set of intervals.

For example, given labelled data such:

| Value | Label   |

|-------| ------- |

| 1     | true |

| 40    | true |

| 100   | false |

| 101   | false |

We might discover the intervals:

- less than 100 (true)

- 100 or more (false)

This is a reimplementation of the 1R quantization algorithm described in [Holte (1993)](https://link.springer.com/article/10.1023%2FA%3A1022631118932). It is a complement to .

# Documentation and examples

- [API reference and usage](https://docs.rs/oner_quantize/)

- An example application: 

# License

Copyright 2020 Richard Dallaway

This Source Code Form is subject to the terms of the Mozilla Public

License, v. 2.0. If a copy of the MPL was not distributed with this

file, You can obtain one at .