Comparison of Time Series Classifications

One application, multiple algorithms, multiple datasets, a simple interface.

Numerous Available Datasets

Add your own as well.

Multiple Classification Algorithms Available

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Time Series

A time series (TS) is a sequence of data points collected at constant time intervals. Time series are used to analyze trends, patterns, and dependencies between data that change over time.

Time series are widely used in prediction, anomaly detection, and pattern recognition across various industries such as finance, healthcare, and engineering.

Classification

Classification, in a general sense, is a process of assigning classes. With the possible classes known in advance, the classification task will assign one of these classes to the current time series.

Our Project

Our project addresses a need for comparison. Indeed, there are many time series classification algorithms, and comparing them can be tedious.

Our tool offers an intuitive and simple interface, allowing this comparison in one place. The application is designed to be modular, offering several classification algorithms by default, and also the possibility to add your own.

The results are presented in a way that facilitates their comparison.

Interface

Find the screenshots of our interface below.

Interface

Home Page

Interface

Experience Type Selection

Classification

Classification Page

Classification

Example Selection

Documentation

Documentation Page

Import

Import Page

Results

Results Page

Technologies

Python
Python

Programming Language

Git
Git

Version Control System

Django
Django

Python Web Framework

HTML
HTML

Markup Language

Our Team

Team Member 1
Charlery Yorick

Backend

Team Member 2
Yuan Mengxin

Frontend