文件名称：TopicModelAlgorithms:主题模型实现的合并集合
文件大小：3.84MB
文件格式：ZIP
更新时间：2024-05-20 15:22:40
seed statistical-learning topic-modeling concept computational-linguistics
笔记： This is a research code and is developed incrementally. So, it is not well organized and also some parts are not relevant. For example: the perplexity computation function is incorrect, if you need this then you need to modify the code or contact the authors. This code is partially commented. Use it at your own risk. 主题模型实现的合并集合 Java包TopicModelAlgorithms用于为使用Java语言的主题模型实现提供替代方法。 高度赞赏有关TopicMo
【文件预览】：
TopicModelAlgorithms-HEAD
----.gitignore(6B)
----data()
--------seed-1.txt(8B)
--------seed-0.txt(5B)
--------corpus2.txt(223KB)
--------seed-2.txt(8B)
----src()
--------models()
--------util()
----.classpath(483B)
----.settings()
--------org.eclipse.jdt.core.prefs(598B)
----README.md(4KB)
----.project(396B)
----lib()
--------commons-io-2.4.jar(181KB)
--------stanford-parser.jar(3.85MB)
--------args4j-2.0.6.jar(35KB)
----licenses()
--------jLDADMMLicense.txt(854B)
--------TopicModelAlgorithmsLicense.txt(164B)