How does Naive Bayes work in spam filtering?
An example of an AI chatbot conversation about Naive Bayes in spam filtering.
Can you explain how Naive Bayes is used in spam filtering?
Sure! Naive Bayes is a probabilistic algorithm that classifies emails as spam or not based on the presence of certain words.
How does it determine if an email is spam?
It calculates the probability of an email being spam based on the frequency of words in the email compared to known spam and non-spam emails.
What are the advantages of using Naive Bayes for this?
It's simple, fast, and works well with large datasets, making it efficient for real-time spam filtering.
Are there any limitations to this method?
Yes, it assumes that all features are independent, which may not always be the case in real-world scenarios.
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