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    Model of Early Intervention Using Machine Learning: Predicting Monkeypox Pandemic 

    Nieto-Chaupis, Huber (IEEE, 2022)
    This paper presents a model of intervention at the first phases of global pandemic using the criteria of Mitchell that simplifies to some extent the philosophy of Machine Learning. These criteria are projected onto the ...
    Acceso restringido
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    Machine Learning and Bayes Probability For Detecting Camouflaged Mini Pandemic at the Waves of Covid-19 

    Nieto-Chaupis, Huber (IEEE, 2022)
    This paper present a methodology based at Machine Learning and a theory backed by the Bayes probability to identify rare strains that might not be in coherence with the corona virus. By using the criteria of Tom Mitchell ...
    Acceso restringido
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    The Approach of Machine Learning to Optimize the Bank-Customer Interaction at Pandemic Epochs 

    Nieto-Chaupis, Huber (IEEE, 2022)
    Along the pandemic created by the Corona virus 2019 (Covid-19 in shorthand), the global economy was observed to experience various turbulent months that were reflected by the increasing of unemployment and the apparition ...
    Acceso restringido

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    Author
    Nieto-Chaupis, Huber (3)
    SubjectCOVID-19 (3)
    Machine learning (3)
    Pandemics (3)
    Behavioral sciences (1)Computational modeling (1)Computer viruses (1)Convolutional (1)Entropy (1)Learning (artificial intelligence) (1)Machine learning algorithms (1)... View MoreDate2022 (3)

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