Machine learning methods for generating high dimensional discrete datasets

Autor: Manco, Giuseppe, Ritacco, Ettore, Rullo, Antonino, Saccà, Domenico, Serra, Edoardo

Publikováno v: WILEY INTERDISCIPLINARY REVIEWS-DATA MINING AND KNOWLEDGE DISCOVERY 12 (2022). doi:10.1002/widm.1450
info:cnr-pdr/source/autori:Manco, Giuseppe; Ritacco, Ettore; Rullo, Antonino; Sacca, Domenico; Serra, Edoardo/titolo:Machine learning methods for generating high dimensional discrete datasets/doi:10.1002%2Fwidm.1450/rivista:WILEY INTERDISCIPLINARY REVIEWS-DATA MINING AND KNOWLEDGE DISCOVERY/anno:2022/pagina_da:/pagina_a:/intervallo_pagine:/volume:12

The development of platforms and techniques for emerging Big Data and Machine Learning applications requires the availability of real-life datasets. A possible solution is to synthesize datasets that reflect patterns of real ones using a two-step app

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5d82fb615c0117bbac3e074b3ac57632
http://www.cnr.it/prodotto/i/465111

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