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使用 Homebrew, MacPorts 安装 gibbslda

查看 gibbslda 的安装路径、可执行文件、元数据以及面向 AI 代理工作流的安全说明。

安装

其他安装命令

macOS

Homebrew已验证 · 100%
brew install gibbslda

local Homebrew formula metadata

MacPorts已验证 · 94%
sudo port install gibbslda

MacPorts ports tree · math/gibbslda/Portfile · 来源: api.github.com

概览

软件包摘要

Library wrapping imlib2's context API

命令和别名

  • lda

历史

项目历史与用法

GibbsLDA++ is a C/C++ implementation of Latent Dirichlet Allocation using Gibbs sampling for parameter estimation and inference. It belongs to the late-2000s generation of compact research toolkits for topic modeling.

项目历史

The official SourceForge project identifies GibbsLDA++ as a beta C/C++ Gibbs-sampling LDA implementation by pxhieu. The project was registered in July 2007, and its file area shows the manual, case-study material, and 0.2 source distribution published in July and August 2007.

采用历史

GibbsLDA++ was useful because LDA had become a common model for hidden topic structures while many researchers still wanted a small command-line implementation. The supplied package metadata shows it carried by Homebrew and MacPorts, reflecting a preservation-style package footprint for older scientific workflows.

使用方式

Practitioners use the `lda` executable to estimate LDA models and infer topic distributions from text corpora. The official project description emphasizes large-scale text data collections, Gibbs sampling, and console/terminal use.

为什么软件包爱好者会关心

For package maintainers, GibbsLDA++ is a small legacy scientific CLI whose main value is reproducibility. Keeping it packaged lets old scripts and papers continue to depend on a stable `lda` executable rather than a broad machine-learning framework.

时间线

  • 2007: SourceForge project registered.
  • 2007: Documents published on SourceForge.
  • 2007: GibbsLDA++ 0.2 source and case-study files published.
  • 2013: SourceForge project page records a later project update.

Related projects

  • GibbsLDA++ is related to JGibbLDA from the same topic-modeling lineage, LDA research implementations, and other C/C++, Java, Matlab, and Python topic-modeling packages.

安全态势

风险级别:绿色

library-like package without higher-risk signals.

风险分类器

绿色 风险 · 低 置信度 · appliance

原因

  • library-like package without higher-risk signals

信号

  • metadata:library-like

安装行为

  • 未记录 Homebrew bottle 元数据。

建议审查

在无人值守的代理使用前,请检查该工具是否读取明文凭据、写入远程状态、发布制品或调用插件。

可执行文件

已安装的可执行文件

命令类型暴露范围备注
lda可执行文件已索引可执行文件从本地可执行文件索引发现。

新鲜度

版本和新鲜度

这些信号区分页生成时间、软件包管理器活动和上游发布比较。只有存在证据 URL 和可比较版本时,才会提示版本落后。

页面生成时间2026-08-03
管理器版本0.2
管理器更新时间
本地数据未知
上游不可用
检测到的最新版本未检测到
  • OK没有生成新鲜度警告。

安装元数据

软件包元数据

软件包键brew:gibbslda
版本0.2
软件包管理器Homebrew
主页https://gibbslda.sourceforge.net/
Bottle未记录
服务未声明

源数据库匹配

其他软件包管理器记录

匹配项来自外部软件包管理器索引,并与本地 Automic Vault 软件包链接分开显示。

MacPorts95%

gibbslda

sudo port install gibbslda
  • normalized package name match
  • 匹配方式:Gibbslda
MacPorts ports tree · api.github.com · MacPorts ports tree: math/gibbslda/Portfile from https://api.github.com/repos/macports/macports-ports/git/trees/master?recursive=1

来源线索

由仓库数据生成

此页面由 av-webscripts/generate-pkg-sqlite.py 生成的私有软件包 SQLite 工件提供。

使用的来源

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