Git Product home page Git Product logo

sentencesimilarity's Introduction

使用说明

1.train.py

该文件是存放 训练方法的类

2.test.py

该文件是用来测试 训练方法的类的逻辑

3.test2.py

该文件是用来形成word2vec模型,如 test2.model

4.splitDescription.py

把csv的句子导入到一个文本 形成语料库

5.cross_validation.py

用来测试最终结果

使用顺序说明

首先splitDescription.py 生成语料库
然后test2.py 形成 word2vec 模型
其次查看train.py 里面存放 训练逻辑
然后test.py 尝试导入一两个句子或者词组 查看train.py是否正确
最后cross_validation.py 查看句子正确率

sentencesimilarity's People

Contributors

risanli avatar

Watchers

James Cloos avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.