Machine Learning Mock Interview
Practice 20 Machine Learning interview questions covering algorithms, model evaluation, and deep learning fundamentals.
Question 9 of 20
Bayes' Theorem is often described as 'Naive.' Why is Bayes naive?
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William Swansen has worked in the employment assistance realm since 2007. He is an author, job search strategist, and career advisor who helps individuals worldwide and in various professions to find their ideal careers.
This is a follow-up to the question 'Can you define Bayes' Theorem and discuss how it is useful in the context of machine learning?'. Anytime you provide an answer during an interview, you can anticipate a follow-up question. This indicates that the interviewer would like to explore the topic in more depth or that the subject being discussed is important to the organization. Keeping your original answers brief and to the point will encourage follow-up questions. This also helps you to focus on what is important in all of your answers.
William Swansen has worked in the employment assistance realm since 2007. He is an author, job search strategist, and career advisor who helps individuals worldwide and in various professions to find their ideal careers.
"Even though the Bayes' Theorem has many practical applications, it is considered naive because it assumes conditions that are not indicated by the data. This is due to the conditional probability being calculated as a product of the components' individual probabilities. The result is an assumption of independence of the features, which could not occur in the real world."
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