Search Results for author: Dominique Gay

Found 6 papers, 0 papers with code

Automatic Feature Engineering for Time Series Classification: Evaluation and Discussion

no code implementations2 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.

Descriptive Feature Engineering +2

Interpretable Feature Construction for Time Series Extrinsic Regression

no code implementations15 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.

Benchmarking regression +2

Predictive K-means with local models

no code implementations16 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.

Clustering Explainable Artificial Intelligence (XAI)

Should we Reload Time Series Classification Performance Evaluation ? (a position paper)

no code implementations8 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.

General Classification Position +3

Cats & Co: Categorical Time Series Coclustering

no code implementations6 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.

Clustering Model Selection +2

Country-scale Exploratory Analysis of Call Detail Records through the Lens of Data Grid Models

no code implementations20 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.

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