Time Series Annotation using Active Learning

Overview

This repository contains all the materials and code related to our major project for the 6th semester, titled "Time Series Annotation using Active Learning". The project delves into the domain of time series annotation, focusing on the challenges and potential of integrating active learning techniques.

Mentor

• Dr. Ankit Sharma

Team Members

• Vinamra Vashishth
• Shashank Mishra
• Himanshu Chittora

Contents

1. Code: All the source code used for the project.
2. Setup and Installation: Detailed setup and installation explaining how to run it.

⚠️ Warning: The dataset used in this project is proprietary to Melio.tech and is not available publicly. Unauthorized distribution or use of this dataset is strictly prohibited.

Features

• Time series annotation with a focus on outlier detection and removal.
• Active-learning based time series clustering using Time Series K-Means.
• A web application for practical real-world applications.

Setup and Installation

1. Clone the repository: git clone [repository-link]
2. Navigate to the project directory: cd [project-directory]
3. Install the required packages: pip install -r requirements.txt
4. Run the application: python main.py

Achievements

• This project was presented as our major project for the 6th semester.

Acknowledgements

We would like to express our gratitude to our mentor, Dr. Ankit Sharma, for his guidance and support throughout the project.