Cookies
O website necessita de alguns cookies e outros recursos semelhantes para funcionar. Caso o permita, o INESC TEC irá utilizar cookies para recolher dados sobre as suas visitas, contribuindo, assim, para estatísticas agregadas que permitem melhorar o nosso serviço. Ver mais
Aceitar Rejeitar
  • Menu
    Publicações

    Publicações por João Gama

    1998

    Local Cascade Generalization

    Autores
    Gama, J;

    Publicação
    Proceedings of the Fifteenth International Conference on Machine Learning (ICML 1998), Madison, Wisconsin, USA, July 24-27, 1998

    Abstract

    1997

    Probabilistic Linear Tree

    Autores
    Gama, J;

    Publicação
    Proceedings of the Fourteenth International Conference on Machine Learning (ICML 1997), Nashville, Tennessee, USA, July 8-12, 1997

    Abstract

    1996

    Regression by Classification

    Autores
    Torgo, L; Gama, J;

    Publicação
    Advances in Artificial Intelligence, 13th Brazilian Symposium on Artificial Intelligence, SBIA '96, Curitiba, Brazil, October 23-25, 1996, Proceedings

    Abstract

    2011

    Using GNUsmail to Compare Data Stream Mining Methods for On-line Email Classification

    Autores
    Cejudo, JMC; García, MB; Bueno, RM; Gama, J; Bifet, A;

    Publicação
    Proceedings of the Second Workshop on Applications of Pattern Analysis, WAPA 2011, Castro Urdiales, Spain, October 19-21, 2011

    Abstract

    2000

    Thesis: Inductive learning classification algorithms

    Autores
    Gama, J;

    Publicação
    AI Commun.

    Abstract

    2011

    Learning from medical data streams: An introduction

    Autores
    Rodrigues, PP; Pechenizkiy, M; Gaber, MM; Gama, J;

    Publicação
    CEUR Workshop Proceedings

    Abstract
    Clinical practice and research are facing a new challenge created by the rapid growth of health information science and technology, and the complexity and volume of biomedical data. Machine learning from medical data streams is a recent area of research that aims to provide better knowledge extraction and evidence-based clinical decision support in scenarios where data are produced as a continuous flow. This year's edition of AIME, the Conference on Artificial Intelligence in Medicine, enabled the sound discussion of this area of research, mainly by the inclusion of a dedicated workshop. This paper is an introduction to LEMEDS, the Learning from Medical Data Streams workshop, which highlights the contributed papers, the invited talk and expert panel discussion, as well as related papers accepted to the main conference.

    FecharLer Abstract
    • 76
    • 89