Anomaly Detection

Content

• How to run it
• Introduction and Motivation
• Libraries Used
• Project Report
• Additional Resources

How to run it

• Pull the src code
• Open terminal
• Navigate to the folder
• Run

    make docker_build
    make docker_run

• For results: AnomalyDetectionProject > data > .png files

Introduction and Motivation

This repo was created as project for CPSC-473: Introduction to Data Mining course. For the course my classmate @TheLostLight and I created a simple anomaly detection python project. Out of vast variety of anomaly detection techniques available we picked Guassian Distribution. The reason why we selected Guassian Distribution is because it is a very popular, easy to explain and implement. If you are interested in more about this check out the project report below.

Libraries Used

For normal user program:

• python3
• pandas
• numpy
• matplotlib
• openpyxl

For dev (including above libraries):

• isort
• black
• flake8
• safety
• pdoc3

Project Report

Link to project report

Additional Resources

• Precision and Recall
• Intro to Anomaly Detection
• Step by step guide: Anomaly detection Algorithm
• Cross Validation