wonderer007 / Naive Bayes Classifier
Naive Bayes classifier is classification algorithm. It uses Naive based Bernoulli and Multinomial equation to classify documents(Text) as ham or spam.
Programming Languages
java
68154 projects - #9 most used programming language
Projects that are alternatives of or similar to Naive Bayes Classifier
Turf
A modular geospatial engine written in JavaScript
Stars: ✭ 6,659 (+110883.33%)
Mutual labels: algorithm
Vscode Leetcode
Solve LeetCode problems in VS Code
Stars: ✭ 6,982 (+116266.67%)
Mutual labels: algorithm
Examples
A collection of TLA+ specifications of varying complexities
Stars: ✭ 720 (+11900%)
Mutual labels: algorithm
Imageai
A python library built to empower developers to build applications and systems with self-contained Computer Vision capabilities
Stars: ✭ 6,734 (+112133.33%)
Mutual labels: algorithm
Seq2seq Chatbot
Chatbot in 200 lines of code using TensorLayer
Stars: ✭ 777 (+12850%)
Mutual labels: corpus
Light Tips
Some code tips about algorithms, php and more 🔥
Stars: ✭ 705 (+11650%)
Mutual labels: algorithm
Numerical Computing Is Fun
Learning numerical computing with notebooks for all ages.
Stars: ✭ 730 (+12066.67%)
Mutual labels: algorithm
Nlp chinese corpus
大规模中文自然语言处理语料 Large Scale Chinese Corpus for NLP
Stars: ✭ 6,656 (+110833.33%)
Mutual labels: corpus
Algorithm
Algorithm is a library of tools that is used to create intelligent applications.
Stars: ✭ 787 (+13016.67%)
Mutual labels: algorithm
Dc Notes
自己的学习笔记。包含：21届秋招经历、🐂客面经问题按照频率总结、Java一系列知识、数据库、分布式、微服务、前端、技术面试、工具教程等(持续更新)
Stars: ✭ 714 (+11800%)
Mutual labels: algorithm
Pyswarms
A research toolkit for particle swarm optimization in Python
Stars: ✭ 742 (+12266.67%)
Mutual labels: algorithm
Competitivequestion
Question solved on various competitive sites 🤘
Stars: ✭ 5 (-16.67%)
Mutual labels: algorithm
Rake Nltk
Python implementation of the Rapid Automatic Keyword Extraction algorithm using NLTK.
Stars: ✭ 793 (+13116.67%)
Mutual labels: algorithm
Naive-Bayes-classifier
Naive Bayes classifier is classification algorithm. It uses Naive based Bernoulli and Multinomial equation to classify documents(Text) as ham or spam. Currently algorithm is only classifying in two categories but it can be modified to classify a text in N categories.
Project Structure
/jars executable jars if you don't want to run source code
/src/main source code of Naive-Bayes-classifier
/src/corpus contains all data files trainining files and testing files, list of stop words file
you can run project by either importing it in eclipse or using cmd/termianl in java based environment
Using Eclipse
- Import Project in eclipse ( using Existing Project into Workspace option )
- run Train.java (main class) to train you corpus using corpus_root_path as run time argument
- After running Train.java check out Bernouli.out and Multinomail.out files at corpus_root_path. these are model build by bernouli and multinomial calculations
- Now run Test.java (main class ) with corpus_root_path and path_of_file__you_want_to_classify as run time arguments
- Test.java will classify your file with results of both Bernouli and Multinomial
Using Command Line
command line option is easy- cd jars folder
- run command java -jar train1.jar path_of_corpus_folder
- above command will create Bernouli and Multinomial models in corpus folder
- run command java -jar test.jar path_of_corpus_folder path_of_file__you_want_to_classify
- above command will classify your file with results of both Bernouli and Multinomial
Note I will try to push regular updates on algorithm, in case you don't understand anything please hit me out at [email protected] or tweet me @alihaider907 Thank you
Note that the project description data, including the texts, logos, images, and/or trademarks,
for each open source project belongs to its rightful owner.
If you wish to add or remove any projects, please contact us at [email protected].