Detection of Representative Variables in Complex Systems with Interpretable Rules Using Core-Clusters

Detection of Representative Variables in Complex Systems with Interpretable Rules Using Core-Clusters

In this paper, we present a new framework dedicated to the robust detection of representative variables in high dimensional spaces with a potentially limited number of observations. Representative variables are selected by using an original regularization strategy: they are the center of specific va...

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Bibliographic Details
Main Authors: Camille Champion, Anne-Claire Brunet, Rémy Burcelin, Jean-Michel Loubes, Laurent Risser
Format: Article
Language:English
Published: MDPI AG 2021-02-01
Series:Algorithms
Subjects:
feature selection
representative variable detection
interpretable machine learning
regularization
complex data
graph clustering
Online Access:https://www.mdpi.com/1999-4893/14/2/66

Internet

https://www.mdpi.com/1999-4893/14/2/66

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