Melhorar a explicabilidade da rede neural
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Melhorar a explicabilidade da rede neural

Melhorar a explicabilidade da rede neural


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About the Book

A Inteligência Artificial (IA) baseada em redes neuronais é crucial em muitas aplicações, como sistemas de recomendação, tradução de línguas, redes sociais, chatbots, correção ortográfica, etc. No entanto, estas redes são frequentemente criticadas por serem "caixas negras", o que suscita preocupações quanto à sua explicabilidade, especialmente em domínios sensíveis como os cuidados de saúde, a condução autónoma, etc. Os métodos existentes para melhorar a explicabilidade, como a importância das caraterísticas, carecem frequentemente de clareza e interpretabilidade. Para resolver este problema, foi desenvolvida a Rede Neural Orientada para Objectos para Melhorar a Explicabilidade (OONNIE). A OONNIE utiliza a modelação orientada para objectos para combinar a perda e o peso da ligação para calcular a importância das caraterísticas e integra regras específicas do domínio através da extensibilidade da OOP. O modelo enfatiza a transparência algorítmica, detalhando cada passo do treino. Avaliado nas funções XOR e XNOR, o OONNIE apresenta resultados promissores em termos de importância das caraterísticas, redução mais rápida das perdas e previsões melhoradas após a integração das regras do domínio. Isto marca uma contribuição significativa para a IA explicável, tornando o OONNIE uma ferramenta valiosa para o desenvolvimento de sistemas de IA fiáveis.


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Product Details
  • ISBN-13: 9786202371179
  • Publisher: Edicoes Nosso Conhecimento
  • Publisher Imprint: Edicoes Nosso Conhecimento
  • Height: 229 mm
  • No of Pages: 132
  • Returnable: N
  • Weight: 240 gr
  • ISBN-10: 620237117X
  • Publisher Date: 11 Aug 2025
  • Binding: Paperback
  • Language: Portuguese
  • Returnable: N
  • Spine Width: 8 mm
  • Width: 152 mm


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