# mallet を Homebrew, MacPorts でインストール

mallet 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:mallet
```

追加のインストールコマンド:

### macOS

- Homebrew (100%):

```sh
brew install mallet
```

  証拠: local Homebrew formula metadata

- MacPorts (94%):

```sh
sudo port install mallet
```

  証拠: MacPorts ports tree: math/mallet/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:mallet
- **パッケージマネージャ:** Homebrew
- **パッケージマネージャページ:** <https://formulae.brew.sh/formula/mallet>
- **バージョン:** 202108
- **ソース概要:** MAchine Learning for LanguagE Toolkit
- **ホームページ:** <https://mimno.github.io/Mallet/index>
- **リポジトリ:** <https://github.com/mimno/Mallet>
- **上流ドキュメント:** <https://mimno.github.io/Mallet/index>
- **ライセンス:** Apache-2.0
- **ソースアーカイブ:** <https://github.com/mimno/Mallet/releases/download/v202108/Mallet-202108-bin.zip>
- **最終更新:** 2026-06-22T14:05:26-07:00
- **生成日時:** 2026-08-04T22:13:35+00:00

## 実行可能ファイル

- classifier2info (cli)
- csv2classify (cli)
- csv2vectors (cli)
- mallet (cli)
- mallethon (cli)
- prepend-license.sh (cli)
- svmlight2vectors (cli)
- text2classify (cli)
- text2vectors (cli)
- vectors2classify (cli)
- vectors2info (cli)
- vectors2topics (cli)
- vectors2vectors (cli)
- classifier2info (エイリアス)
- csv2classify (エイリアス)
- csv2vectors (エイリアス)
- mallet (エイリアス)
- mallethon (エイリアス)
- prepend-license.sh (エイリアス)
- svmlight2vectors (エイリアス)
- text2classify (エイリアス)
- text2vectors (エイリアス)
- vectors2classify (エイリアス)
- vectors2info (エイリアス)
- vectors2topics (エイリアス)
- vectors2vectors (エイリアス)

## 依存関係

- openjdk

## インストール挙動

- post-install フック: 未定義
- Bottle: 利用可能 対象 all

## バージョンと鮮度

- ページ生成日: 2026-08-04
- マネージャ版: 202108
- マネージャ更新日: 2026-06-22
- ローカルデータ: OK
- 上流リポジトリ: https://github.com/mimno/Mallet
- 情報: No cached GitHub release or tag data was available.
## プロジェクトの歴史と使われ方

MALLET, the MAchine Learning for LanguagE Toolkit, is a Java package and command-line toolkit for statistical natural language processing. Its official documentation describes support for document classification, clustering, topic modeling, information extraction, sequence tagging, and other machine-learning applications to text.

### プロジェクトの歴史

The project is associated with Andrew McCallum's MALLET citation from 2002 and originated in an academic NLP context at UMass. The modern public repository is maintained under the mimno GitHub organization, and the official site identifies it as open source under the Apache 2.0 license.

MALLET became especially visible to digital humanities, information science, and NLP users because it packaged algorithms such as Maximum Entropy classifiers, Conditional Random Fields, Latent Dirichlet Allocation, Pachinko Allocation, and Hierarchical LDA behind reusable Java APIs and shell commands. Its 2.1.0 release in 2026 was described by the maintainers as the first stable release since 2.0.8 in 2016, modernizing the build around Java 17 and Maven.

### 採用の歴史

MALLET's package-manager footprint is modest but important: Homebrew and MacPorts carry it for macOS users who want the historical CLI workflow without building the Java project by hand. The GitHub repository shows roughly a thousand stars and hundreds of forks, which is consistent with a long-lived research toolkit rather than a fast-moving application.

The toolkit's adoption has been strongest where reproducible text-analysis workflows matter: topic-modeling corpora, classroom NLP exercises, digital humanities projects, and research code that wants a known implementation rather than a cloud service.

### 使われ方

The command-line workflow centers on `bin/mallet [command] --option value`, with helper commands for importing text or CSV data, converting data to vectors, training classifiers, classifying new text, and running topic models. The README recommends building with Maven or using binary downloads, then running `bin/mallet --help` or a command-specific help option.

In packages such as Homebrew, MALLET matters because it turns a Java research toolkit into ordinary terminal commands like `mallet`, `text2vectors`, `vectors2topics`, and `csv2classify`, making it scriptable in shell pipelines and notebooks.

### パッケージ好きにとっての重要性

MALLET is a classic example of a research toolkit that became infrastructure for package-manager users: old enough to have stable workflows, specialized enough that vendoring it is annoying, and still useful when a project needs local NLP processing without a server stack.

For package curators, the interesting maintenance points are Java runtime requirements, binary wrapper scripts, and the 2026 shift to Java 17 and Maven. Those details directly affect whether older MALLET recipes keep working on current systems.

### タイムライン

- 2002: Andrew McCallum's official MALLET citation identifies the toolkit.
- 2016: MALLET 2.0.8 became the last stable release before a long quiet period.
- 2021: A serialization-breaking 202108 release changed internal collections and licensing details.
- 2026: MALLET 2.1.0 shipped as the first stable release since 2.0.8, requiring Java 17.

### Related projects

- GRMM was documented as an add-on package for inference in graphical models and CRF training with arbitrary graphical structure.
- MALLET overlaps historically with NLP libraries and topic-modeling stacks, but remains distinctive because it exposes mature algorithms as local Java command-line tools.

### ソース

- <https://github.com/mimno/Mallet>
- <https://github.com/mimno/Mallet/releases>
- <https://mimno.github.io/Mallet/>
- source_facts.package-manager


## 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

## ソースデータベース詳細

- **Source Database:** Homebrew formula API
- **Tap:** homebrew/core
- **Full Name:** mallet
- **Version Scheme:** 0
- **Revision:** 0
- **Bottle Stable Root URL:** <https://ghcr.io/v2/homebrew/core>
- **Deprecated:** no
- **Disabled:** no
- **Keg Only:** no
- **URL Keys:** stable

## 他のパッケージマネージャ記録

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


## 関連リンク

- [Source-control packages](https://pkg.so/ja/source-control-tools/) - Belongs to a source-control command family.
- [MCP tool packages](https://pkg.so/ja/mcp-tools/) - Mentions MCP or Model Context Protocol.
- [AI and agent packages](https://pkg.so/ja/ai-agent-tools/) - Matched AI model, agent, coding-agent, orchestration, or MCP metadata.
- [Terminal utility packages](https://pkg.so/ja/terminal-utilities/) - Matched terminal and command-line workflow metadata.
- [openjdk](https://pkg.so/ja/brew/openjdk/) - Runtime dependency declared by Homebrew.
- [apache-opennlp](https://pkg.so/ja/brew/apache-opennlp/) - Shares pkgdb curated category or tags: ai, cli, java, machine-learning, ml-tools.
- [djl-serving](https://pkg.so/ja/brew/djl-serving/) - Shares pkgdb curated category or tags: ai, cli, java, machine-learning, ml-tools.
- [tinysvm](https://pkg.so/ja/brew/tinysvm/) - Shares pkgdb curated category or tags: ai, classification, cli, machine-learning, ml-tools.
- [tesseract](https://pkg.so/ja/brew/tesseract/) - Shares pkgdb curated category or tags: ai, cli, machine-learning, ml-tools.
- [opencv](https://pkg.so/ja/brew/opencv/) - Shares pkgdb curated category or tags: ai, cli, machine-learning, ml-tools.
- [pytorch](https://pkg.so/ja/brew/pytorch/) - Shares pkgdb curated category or tags: ai, cli, machine-learning, ml-tools.
- [mlx](https://pkg.so/ja/brew/mlx/) - Shares pkgdb curated category or tags: ai, cli, machine-learning, ml-tools.
- [hf](https://pkg.so/ja/brew/hf/) - Shares pkgdb curated category or tags: ai, cli, machine-learning, ml-tools.

## Combined YAML source

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


## ソース

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