# yamcha を Homebrew, MacPorts でインストール

yamcha のインストール経路、実行ファイル、メタデータ、AI エージェント向けセキュリティノートを確認します。

## インストール

```sh
sudo av install brew:yamcha
```

追加のインストールコマンド:

### macOS

- Homebrew (100%):

```sh
brew install yamcha
```

  証拠: local Homebrew formula metadata

- MacPorts (94%):

```sh
sudo port install yamcha
```

  証拠: MacPorts ports tree: textproc/yamcha/Portfile from https://api.github.com/repos/macports/macports-ports/git/trees/master?recursive=1

## パッケージ情報

- **パッケージキー:** brew:yamcha
- **パッケージマネージャ:** Homebrew
- **バージョン:** 0.33
- **ソース概要:** NLP text chunker using Support Vector Machines
- **ホームページ:** <http://chasen.org/~taku/software/yamcha/>
- **最終更新:** 2026-07-11T12:24:37-04:00
- **生成日時:** 2026-08-03T19:37:03+00:00

## 実行可能ファイル

- yamcha (エイリアス)
- yamcha-config (エイリアス)
- yamcha-mkmodel (エイリアス)

## インストール挙動

- Bottle: 利用不可

## バージョンと鮮度

- ページ生成日: 2026-08-03
- マネージャ版: 0.33
## プロジェクトの歴史と使われ方

YamCha, Yet Another Multipurpose CHunk Annotator, is Taku Kudo's open-source text chunker built around support vector machines. It belongs to the pre-deep-learning generation of NLP packages where feature templates, chunk encodings, and SVM training pipelines were packaged as reusable command-line tools.

### プロジェクトの歴史

The official YamCha page describes it as a generic, customizable text chunker for POS tagging, named-entity recognition, base noun phrase chunking, and text chunking. It says the system used support vector machines and was the same system that performed best in the CoNLL-2000 shared task and a BaseNP chunking task.

The YamCha news log records an initial 0.1 release in July 2001, followed by a steady 2002-2005 sequence that added multi-class strategies, memory savings for large models, C API support, PKE acceleration, experimental Perl/Python/Ruby modules, 64-bit support, and bug fixes. The project page was last revised in late 2005, matching the period when SVM chunkers were a mainstream statistical NLP approach.

### 採用の歴史

YamCha's adoption came through NLP research and language-processing pipelines rather than general developer tooling. The companion ACL paper, Chunking with Support Vector Machines, connects the software to the 2001 NAACL work by Kudo and Matsumoto and to the then-current practice of comparing chunkers on shared tasks.

The package remained relevant in Unix package managers because it bundled training and decoding commands plus a C/C++ library around TinySVM-era models. For users maintaining older NLP experiments, YamCha is a reproducibility and compatibility artifact as much as a current modeling choice.

### 使われ方

Typical use is to prepare token-per-line training or test data with feature columns and chunk labels, train a model with YamCha's template-driven SVM pipeline, and run the `yamcha` decoder or `yamcha-mkmodel` tooling. The official documentation emphasizes feature windows, parsing direction, pairwise versus one-vs-rest multiclass strategies, partial chunking, and model conversion for faster classification.

### パッケージ好きにとっての重要性

YamCha is historically significant because it packages a specific research-era NLP method into a reusable Unix tool. It sits beside ChaSen, TinySVM, CaboCha, CRF++, and MeCab in Taku Kudo's ecosystem of compact Japanese/NLP-oriented C and C++ tools that escaped academia into package managers.

### タイムライン

- 2001: Kudo and Matsumoto published Chunking with Support Vector Machines at NAACL, and YamCha 0.1 was released in July.
- 2002: YamCha 0.2 added multi-class strategy selection, memory savings for large model files, and broader compiler support.
- 2004: YamCha 0.30 added PKE acceleration and a C API; 0.31 added experimental Perl, Python, and Ruby modules.
- 2005: YamCha 0.33 added experimental 64-bit support and bag-of-words features.

### Related projects

- TinySVM is a direct dependency named by the official installation instructions.
- ChaSen, CaboCha, CRF++, and MeCab are related Taku Kudo or Japanese NLP tools from the same broader ecosystem.

### ソース

- <http://chasen.org/~taku/software/yamcha/>
- <https://aclanthology.org/N01-1025/>


## セキュリティノート

narrow executable package without higher-risk signals.

- **Geiger リスク:** グリーン / 低
- narrow executable package without higher-risk signals

## 他のパッケージマネージャ記録

- MacPorts - yamcha: normalized package name match | MacPorts ports tree: textproc/yamcha/Portfile from https://api.github.com/repos/macports/macports-ports/git/trees/master?recursive=1


## Combined YAML source

View the package source record on GitHub. [combined/yamcha.yml](https://github.com/mxcl/pkgdb/blob/main/combined/yamcha.yml)


## ソース

- pkg.so package database
- Geiger risk classifier
- curated package history
- pkgdb category and tag curation
- external package-manager database matches
- cross-ecosystem install command graph