Explain Bayes classifier with the help of a suitable example. Also dis

Question

Explain Bayes classifier with the help of a suitable example. Also discuss its properties

25 Jul 2024

Answer :

Word Count : 366

The Bayes classifier, also known as the Naive Bayes classifier, is a probabilistic model based on Bayes' Theorem, which provides a way to classify data by calculating the probability of a data point belonging to a particular class. It is especially popular in digital image processing and computer vision due to its simplicity and efficiency.

Bayes Classifier Explained:

Bayes' Theorem is expressed as:

\[ P(C | X) = \frac{P(X | C) \cdot P(C)}{P(X)} \]

Where:
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