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freq: Are you ready to get freaky?
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freq: Are you ready to get freaky?
This library provides a way to train a model that predicts the "randomness" of an input ByteString.
[Skip to Readme]
Downloads
- freq-0.1.1.tar.gz [browse] (Cabal source package)
- Package description (as included in the package)
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For package maintainers and hackage trustees
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| Versions [RSS] | 0.0.0, 0.1.0.0, 0.1.0.1, 0.1.0.2, 0.1.0.3, 0.1.0.4, 0.1.1 |
|---|---|
| Dependencies | base (>=4.9 && <4.13), binary (>=0.8 && <0.11), bytestring (>=0.10 && <0.11), containers (>=0.5 && <0.7), deepseq (>=1.4 && <1.5), primitive (>=0.6.4 && <0.7) [details] |
| Tested with | ghc ==8.2.1, ghc ==8.2.2, ghc ==8.4.1, ghc ==8.4.2 |
| License | MIT |
| Author | chessai |
| Maintainer | chessai <chessai1996@gmail.com> |
| Uploaded | by chessai at 2019-04-29T20:38:29Z |
| Category | Text, Data |
| Home page | https://github.com/chessai/freq |
| Bug tracker | https://github.com/chessai/freq/issues |
| Source repo | head: git clone https://github.com/chessai/freq.git -b master |
| Distributions | |
| Downloads | 3619 total (18 in the last 30 days) |
| Rating | (no votes yet) [estimated by Bayesian average] |
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| Status | Docs available [build log] Last success reported on 2019-04-29 [all 1 reports] |
Readme for freq-0.1.1
[back to package description]freq
About
This is a simple cryptanalytic frequency analysis tool that uses english character digrams as a probabilistic model for scoring ByteStrings according to their randomness (0..1, 0 being the most random, 1 being the least random).
Uses
I currently use this to validate domain names, and so the training data available consists of about 6.5 Megabytes of Public Domain 19th and 20th century English novels. You can feed any training data you wish to 'freq' to achieve different results.