主题识别模型
Project description
pyTopicModel
使用Gensim框架,根据摘要(abstract)和标题(title)来实现主题算法
1、下载
pip install pyunit-topicmodel
2、使用
> topic -h
usage: 主题模型
输入主题模型需要的参数
positional arguments:
{train,predict} 选择程序模式
optional arguments:
-h, --help show this help message and exit
-d D 保存结果的文件夹
训练:
训练模型参数
-p P 加载分析的数据路径
-a A 摘要列名
-t T 标题列名
-r R R 主题数取值范围:至少是1
预测:
预测模型参数
-k K 预测主题数
3、训练模型
topic train -p 专利-医学其他领域.xlsx -a abo -t tio -d data -r 10 67
4、预测LDA
topic predict -d data -k 40
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
pyunit-topicmodel-1.0.2.tar.gz
(12.8 kB
view details)
Built Distribution
File details
Details for the file pyunit-topicmodel-1.0.2.tar.gz
.
File metadata
- Download URL: pyunit-topicmodel-1.0.2.tar.gz
- Upload date:
- Size: 12.8 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.9.16
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 15e36d688fe23e9188df621de5a538d870627dcf3c4e8b4a709c2f000a5fb9fd |
|
MD5 | 6e5918bab1f551e475fa77b8740bbf50 |
|
BLAKE2b-256 | 9fc53e205101c59756ddfafa1533310e312b91d64b279eb6d880aef022d9ced1 |
File details
Details for the file pyunit_topicmodel-1.0.2-py3-none-any.whl
.
File metadata
- Download URL: pyunit_topicmodel-1.0.2-py3-none-any.whl
- Upload date:
- Size: 14.8 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.9.16
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | b4191add9dd09404e0f7cab2d2432543aa15a0940c01e81368ac82f027d54ed1 |
|
MD5 | 44bc7cf3839ca5469afecb58940afc1d |
|
BLAKE2b-256 | fa85c14bbcbfe0bbdc9de212adf8ce34b9b04f93419f3c9c73bd6172f39af060 |