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Confusion matrices and derived metrics provide a comprehensive framework for the evaluation of model performance in machine learning. These are well-known and extensively employed in the supervised learning domain, particularly classification. Surpri
Externí odkaz:
http://arxiv.org/abs/2304.01450
Autor:
Jaskowiak, Pablo Andretta
O desenvolvimento da tecnologia de microarray tornou possível a mediçao dos níveis de expressão de centenas ou até mesmo milhares de genes simultaneamente para diversas condições experimentais. A grande quantidade de dados disponível gerou a
The Area Under the the Receiver Operating Characteristics (ROC) Curve, referred to as AUC, is a well-known performance measure in the supervised learning domain. Due to its compelling features, it has been employed in a number of studies to evaluate
Externí odkaz:
http://arxiv.org/abs/2009.02400
Autor:
Jaskowiak, Pablo Andretta
Clustering plays an important role in the exploratory analysis of data. Its goal is to organize objects into a finite set of categories, i.e., clusters, in the hope that meaningful and previously unknown relationships will emerge from the process. No
Publikováno v:
In Methods 1 January 2018 132:42-49
Akademický článek
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Autor:
Adachi, Felipe de Pontes
Publikováno v:
Repositório Institucional da UFSC
Universidade Federal de Santa Catarina (UFSC)
instacron:UFSC
Universidade Federal de Santa Catarina (UFSC)
instacron:UFSC
Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico de Joinville, Programa de Pós Graduação em Engenharia de Sistemas Eletrônicos, Joinville, 2019. A demanda por robustez e segurança na operação de veículos
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______3056::170df8069bb222c8fa667c51ffd63424
https://repositorio.ufsc.br/handle/123456789/215579
https://repositorio.ufsc.br/handle/123456789/215579