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

The Bayes classifier is a probabilistic classifier based on Bayes’ Theorem, which relates current evidence to prior knowledge to make predictions. In the context of Digital Image Processing and Computer Vision, it is commonly used for tasks like object recognition and image classification.

Bayes' Theorem is given by:

$$
P(C|X) = \frac{P(X|C)P(C)}{P(X)}
$$

Where:

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