8 citations · 18 across the 6 of their papers we have counts for
6 papers
Automatic Feature Engineering for Time Series Classification: Evaluation and Discussion
Aurélien Renault, Alexis Bondu, Vincent Lemaire +1
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. Indee…
Interpretable Feature Construction for Time Series Extrinsic Regression
Dominique Gay, Alexis Bondu, Vincent Lemaire +1
Supervised learning of time series data has been extensively studied for the case of a categorical target variable. In some application domains, e.g., energy, environment and healt…
Predictive K-means with local models
Vincent Lemaire, Oumaima Alaoui Ismaili, Antoine Cornuéjols +1
Supervised classification can be effective for prediction but sometimes weak on interpretability or explainability (XAI). Clustering, on the other hand, tends to isolate categories…
Should we Reload Time Series Classification Performance Evaluation ? (a position paper)
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, evaluat…
Cats & Co: Categorical Time Series Coclustering
Dominique Gay, Romain Guigourès, Marc Boullé +1
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 model…
Country-scale Exploratory Analysis of Call Detail Records through the Lens of Data Grid Models
Romain Guigourès, Dominique Gay, Marc Boullé +2
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:…