Recent advances in multiway data modeling for classification issues

AZCARATE, SILVANA MARIELA; DE ARAÚJO GOMES, ADRIANO; MUÑOZ DE LA PEÑA, ARSENIO; GOICOECHEA, HÉCTOR C.

Fundamentals and Applications of Multiway Data Analysis

ElSevier

Año: 2024; p. 193 - 218

This chapter outlines some of the challenging aspects when applying multiway data modeling in classification issues. The theoretical basis and applicative guidelines are detailed. The main analytical platforms and the utilization of the generated data used for classification are briefly discussed from the application point of view. A critical discussion of the advantages concerning the general features of the available algorithms and their underlying models is performed. To illustrate the high potentiality of multiway data modeling in the classification field, a literature example is presented and discussed. Furthermore, the demanded advances in remarkable data fusion strategies about optimally combining multiple data sources in an assortment of fields are revealed.