Naive Bayes

Job Description:


• Multinomial Naive Bayes (MultinomialNB).

– The multinomial Naive Bayes classifier is suitable for classification with discrete features

(e.g., word counts for text classification).

– The multinomial distribution normally requires integer feature counts. However, in

practice, fractional counts such as tf-idf may also work.

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• Gaussian Naive Bayes (GaussianNB).

– Gaussian Naive Bayes supports continuous valued features and models each as conform-

ing to a Gaussian (normal) distribution.

– An approach to create a simple model is to assume that the data is described by a Gaus-

sian distribution with no co-variance (independent dimensions) between dimensions.

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Habilidades: Python, Processamento de dados, Data Analysis

Sobre o Cliente:
( 13 comentários ) Greenbelt, United States

ID do Projeto: #34853472

Concedido a:


Hi, I am artificial intelligence engineer with more 8 years of experience in Data Science & Machine/Deep Learning. I have accomplished projects like yours. Feel free to contact me for further details. Thank you

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