Dear Prof. Joseph Victor,

In my opinion, the primary distinction between a KNN (K-Nearest Neighbors) classifier and a Bayes classifier utilizing KNN PDF (Probability Density Function) estimation lies in their classification approaches. The KNN classifier, being a non-parametric method, categorizes data points by their proximity to others in a feature space without assuming any specific data distribution. It simply assigns the majority class of the k-nearest neighbors to a given data point. On the other hand, the Bayes classifier is a probabilistic model that employs Bayes' theorem for classification based on the likelihood of data points belonging to a specific class.

When the Bayes classifier incorporates KNN PDF estimation, the probability density function for each class is estimated using the KNN method.

Thank You.