This repository contains the code for our paper:
Efficient Time-Series Clustering through Sparse Gaussian Modeling
Dimitris Fotakis, Panagiotis Patsilinakos, Eleni Psaroudaki, Michalis Xefteris
Paper: https://www.mdpi.com/1999-4893/17/2/61
@article{fotakis2024efficient,
title={Efficient Time-Series Clustering through Sparse Gaussian Modeling},
author={Fotakis, Dimitris and Patsilinakos, Panagiotis and Psaroudaki, Eleni and Xefteris, Michalis},
journal={Algorithms},
volume={17},
number={2},
pages={61},
year={2024},
publisher={MDPI}
}
.
├── images # All images
│ ├── dtw # Images for dtw metric
│ | ├── ami # AMI images
│ | ├── ari # ARI images
│ ├── euclidean # Images for euclidean metric
│ | ├── ami # AMI images
│ | ├── ari # ARI images
│ ├── runtime # Runtime images
│ └── additional # Additional images
├── src # Contains the code and the results
│ ├── analytics # Contains the results for each a-m combination
│ ├── results # Contains the avg and std over a for each m and run-times
│ └── ... # source code
├── tables # Tables in tex and md form
│ ├── dtw # Tables for dtw metric
│ | ├── ami # AMI tables
│ | ├── ari # ARI tables
│ ├── euclidean # Tables for euclidean metric
│ | ├── ami # AMI tables
│ | ├── ari # ARI tables
│ └── runtime # Runtime tables
└── ... # README, yml
For our convenience, we have created a bash script that checks the files in the results folder and prints all the combinations of (dataset, metric, with/without preprocessing) that are missing. To run and save the results to a file simply:
bash ./findMissing.sh > missing.txt
or in Linux environment run
chmod u+x findMissing.sh
and then simply
./findMissing.sh > missing.txt