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项目作者： alexantoniogonzalez2

项目描述 ：
A Naive Bayes model built from scratch for grading prediction.
高级语言： Jupyter Notebook
项目地址: git://github.com/alexantoniogonzalez2/naive-bayes-from-scratch.git
创建时间： 2020-07-26T07:59:07Z
项目社区：https://github.com/alexantoniogonzalez2/naive-bayes-from-scratch
开源协议：MIT License
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Naïve Bayes

In this project was developed a Naïve Bayes model from scratch, this is, avoiding to use the built in methods from libraries like Keras or Scikit-learn. The purpose of this restriction is getting a deeper understanding of the mathematical background of the the Naïve Bayes model. Specifically, the model for the prediction of academic grades.

Files

  • The model is available in this Jupyter Notebook.
  • For comparison purposes, a short equivalent version of the model(using Scikit-learn this time) is available here.

Requirements

  • Environment for run a Jupyter Notebook. For example: Jupyter Project. A basic requirement for Jupyter Notebook is Python.
  • The data files utilized in this project should be in a folder named ‘data’ in the same directory that the file ‘Naive Bayes from scratch.ipynb’.

Compatibility

The libraries needed in this project are specified in the Jupyter Notebook. The most general libraries utilized are:

  • Python: 3.7.5
  • Scikit-learn: 0.22

Context

This works is part of the subject COMP90049 Introduction to Machine Learning, 2020 Semester 1, The University of Melbourne.