no code implementations • 2 Aug 2023 • Aurélien Renault, Alexis Bondu, Vincent Lemaire, Dominique Gay
Time Series Classification (TSC) has received much attention in the past two decades and is still a crucial and challenging problem in data science and knowledge engineering.
no code implementations • 15 Mar 2021 • Dominique Gay, Alexis Bondu, Vincent Lemaire, Marc Boullé
Supervised learning of time series data has been extensively studied for the case of a categorical target variable.
no code implementations • 16 Dec 2020 • Vincent Lemaire, Oumaima Alaoui Ismaili, Antoine Cornuéjols, Dominique Gay
We present two new algorithms using this technique and show on a variety of data sets that they are competitive for prediction performance with pure supervised classifiers while offering interpretability of the clusters discovered.
no code implementations • 8 Mar 2019 • Dominique Gay, Vincent Lemaire
Since the introduction and the public availability of the \textsc{ucr} time series benchmark data sets, numerous Time Series Classification (TSC) methods has been designed, evaluated and compared to each others.
no code implementations • 6 May 2015 • Dominique Gay, Romain Guigourès, Marc Boullé, Fabrice Clérot
We suggest a novel method of clustering and exploratory analysis of temporal event sequences data (also known as categorical time series) based on three-dimensional data grid models.
no code implementations • 20 Mar 2015 • Romain Guigourès, Dominique Gay, Marc Boullé, Fabrice Clérot, Fabrice Rossi
Call Detail Records (CDRs) are data recorded by telecommunications companies, consisting of basic informations related to several dimensions of the calls made through the network: the source, destination, date and time of calls.