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Question: 1 / 1980

A key feature of Bayesian filtering is its reliance on what?

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Statistical probabilities

Bayesian filtering's core function is fundamentally based on statistical probabilities. This technique utilizes Bayes' Theorem to calculate the likelihood of a particular event or outcome, such as determining whether an email is spam based on its content. By analyzing the frequency of specific words or phrases in both spam and legitimate emails, Bayesian filtering assigns probabilities to the presence of those elements, allowing for an informed decision on how to classify incoming messages.

The statistical approach allows the filter to adapt over time as more data is processed. As users receive and mark emails as spam or legitimate, the Bayesian filter updates its probability estimates, improving its accuracy in future classifications. This reliance on statistical probabilities is what distinguishes Bayesian filtering from other techniques, making it a powerful tool in identifying and filtering unwanted content effectively.

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Pattern recognition algorithms

Predictive analytics

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