MAT-view: Visualization Tools for Multiple Aspect Trajectory Data Mining
Project description
MAT-view: Visualization Tools for Multiple Aspect Trajectory Data Mining [MAT-Tools Framework]
[Publication] [citation.bib] [GitHub] [PyPi]
The present application offers a set of web tools to support the user in the visualization of multiple aspect trajectories and movelets (the parts of the trajectory that better discriminate a class). Also, present a detailed list of available datasets on a public repository, descriptions of MAT data mining methods, experimental results exploration, environmental and scripting generators. It integrates into a unique platform of the approaches available for multiple aspects trajectories and in general for multidimensional sequence classification into a unique web-based and python library system.
Created on Jun, 2024 Copyright (C) 2024, License GPL Version 3 or superior (see LICENSE file)
Installation
Install directly from PyPi repository, or, download from github. (python >= 3.7 required)
pip install mat-view
Usage
This package enables a environment script to run the web application, just run:
MAT-Web.py
By default Dash will run on http://127.0.0.1:8050/
* In case you have trouble loading any data into the page (or an action is not updating the page), refresh the site and try again.
Citing
If you use mat-view
please cite the following paper:
TODO
Bibtex:
@inproceedings{...}
Collaborate with us
Any contribution is welcome. This is an active project and if you would like to include your algorithm in mat-view
, feel free to fork the project, open an issue and contact us.
Feel free to contribute in any form, such as scientific publications referencing mat-view
, teaching material and workshop videos.
Related packages
This package is part of MAT-Tools Framework for Multiple Aspect Trajectory Data Mining, check the guide project:
- mat-tools: Reference guide for MAT-Tools Framework repositories
And others:
Change Log
This is a package under construction, see CHANGELOG.md
Project details
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