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Lecture Notes - Naive Bayes New PDF

8 Pages·2021·English
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by ['Amandeep Kaur Gahir']| 2021| 8 pages| English

About Lecture Notes - Naive Bayes New

- The document discusses Naive Bayes, a probabilistic classification algorithm. It explains key concepts like probability, conditional probability, joint probability, and Bayes' theorem. - Naive Bayes makes a strong independence assumption that features are conditionally independent given the class. This allows it to estimate probabilities by counting occurrences. - The document provides examples of how Naive Bayes classifies text documents using a bag-of-words representation and calculating posterior probabilities to assign classes. Laplace smoothing helps address zero probabilities.

Detailed Information

Author:['Amandeep Kaur Gahir']
Publication Year:2021
Pages:8
Language:English
Format:PDF
Price:FREE
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