# Part III project Dan Roberts (dr1n22) <[e-mail]>
###### tags: `aeon-part-III`

__Contributor:__ Dan Roberts (dr1n22) <[e-mail]>
__Project:__
__Project length:__ Two semesters
__Supervisors:__ Tony Bagnall, Matthew Middlehurst
__Start date:__ Monday, September 23rd
__End date:__ TBC
__Regular meeting time:__

## Project Summary

## Project Timeline

## Getting started tasks

- [x] Go through the contributor guide on the _aeon_ website (https://www.aeon-toolkit.org/en/stable/contributing.html).
- [x] Set up a development environment, including _pytest_ and _pre-commit_ dependencies. This will make development a lot easier for you, as you must pass the PR tests to have your code merged (https://www.aeon-toolkit.org/en/stable/developer_guide/dev_installation.html).
- [ ] Review some of the important dependencies for developing aeon at a basic level:
- [ ] __scikit-learn__ the interface aeon estimators extend from. We aim to keep as compatile as possible with sklearn tools.
- [ ] __pytest__ for unit testing. Any code added will have to be covered by tests.
- [ ] __sphinx/myst__ for documentation. Adding new functions and classes will have to be added to the API docs.
- [ ] __numba__ for writing efficient functions.
- [x] Make a basic Pull Request (PR) to gain some experience with contributing to _aeon_ through GitHub.
- [ ] Add the project time line objects to this document.

# Make notes of progress here

## Monday 30/9/24 14:00 pm

agree objectives

Look at time series segmentation with an application for human activity recognition.

Papers of interest

1. Time series classification
https://link.springer.com/article/10.1007/s10618-024-01022-1
2. Time series regression
https://link.springer.com/article/10.1007/s10618-024-01027-w

**to do. Tony.**

1. Find links to papers.
2. Contact Arik and Patrick re algorithms
3. Contact Danieli

## Tuesday 8/10/24 12:30 pm

Agree overall structure
#### Semester 1
1. Lit review of segmentation
a. Select desired algorithms to implement
3. Recreation of HAR competition results
4. Define standard for experiment assessment
#### Semester 2
4. Implement selected algorithms
5. Evaluate/assess algorithms on real HAR data (generated by sensors)

## 24/10/24

project meeting: literature review ongoing, need a new algorithm to implement. Tony to pick an algorithm