Processing in machine learning qualitative variables having a very large number of modalities is an opportunity to revisit the theory of optimal scaling and its applications. This revisitation starts with the pioneers of scaling in statistics, psychometrics, and psychology before moving on to more contemporary treatments of scaling that fall within the realm of machine learning and neural networks.
Old and New Perspectives on Optimal Scaling / Abdi, Hervé; DI CIACCIO, Agostino; Saporta, Gilbert. - (2023), pp. 131-154. - BEHAVIORMETRICS. [10.1007/978-981-99-5329-5_9].
Old and New Perspectives on Optimal Scaling
Agostino Di Ciaccio;
2023
Abstract
Processing in machine learning qualitative variables having a very large number of modalities is an opportunity to revisit the theory of optimal scaling and its applications. This revisitation starts with the pioneers of scaling in statistics, psychometrics, and psychology before moving on to more contemporary treatments of scaling that fall within the realm of machine learning and neural networks.File allegati a questo prodotto
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