Which statements about Naive Bayes are true? (Select all that apply.)

Question

BlackTom AI · Accepted Answer

The question asks which statements about Naive Bayes are true, and to select all that apply. 
Option 1: 'NB assumes feature independence' — This is a core assumption of the Naive Bayes classifier: it treats features as conditionally independent given the class. While this simplifying assumption is often violated in practice, the model still works surprisingly well in many settings, especially with text data, which makes this statement true. 
Option 2: 'NB predicts using posterior probability calculations' — Naive Bayes uses Bayes’ theorem to compute the posterior probability of each class given the observed features, and then selects the class with the highest posterior. This is a fundamental mechanism of NB, so this statement is true. 
Option 3: 'NB sums TF-IDF scores and picks highest' — This describes a scoring mechanism not used by Naive Bayes. TF-IDF scores are features used in vector space models and can feed other classifiers, but NB combines feature likelihoods with priors, not a simple sum of TF-IDF scores. This makes the statement false. 
Option 4: '“48” indicates bullish predicted bearish' — This option appears to reference a specific numeric label or interpretation not inherent to Naive Bayes theory. Without a defined mapping from numbers to classes, this statement is unfounded in the NB context and is false. 
Option 5: 'TF-IDF is required because NB cannot use raw counts' — Naive Bayes can operate on raw term counts or on term frequencies; using TF-IDF is not a requirement, and in some cases raw counts can even be more appropriate. Therefore this statement is incorrect. 
Option 6: 'NB predicts using posterior probability calculations' — This repeats Option 2 and is true for the same reason: NB uses posterior probabilities to decide the class. 
In summary, the true statements are those related to the independence assumption and the use of posterior probabilities for prediction, while the other options describe methods or interpretations not characteristic of standard Naive Bayes workflows.

IS 4487-006 Fall 2025 Final Exam December 10 from 10:30 to 12:30

Which statements about Naive Bayes are true? (Select all that apply.)

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Naïve Bayes Classifier can be used for ______________________. Select all that apply for full marks.

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