Virtual Labs

Movie Review Sentiment Analysis using Naïve Bayes

What does P(A|B) represent in Bayes' Theorem?

a: The prior probability of event A Explanation

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b: The probability of event B occurring Explanation

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c: The probability of event A given event B Explanation

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d: The likelihood of event B given A Explanation

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Why is Naive Bayes considered 'naive'?

a: It requires very small datasets Explanation

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b: It assumes all features are dependent on each other Explanation

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c: It assumes all features are independent of each other Explanation

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d: It ignores probabilities during classification Explanation

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What problem does Laplace smoothing solve in Naive Bayes?

a: Overfitting caused by too much training data Explanation

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b: Zero probability for words not seen in the training data Explanation

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c: Slow training speed Explanation

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d: Incorrect ordering of word tokens Explanation

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Why are log probabilities used in Naive Bayes?

a: To make calculations faster than normal probability Explanation

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b: To convert numbers into text Explanation

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c: To avoid numerical underflow from multiplying many small probabilities Explanation

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d: Because logs improve text preprocessing Explanation

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Which of the following is an important text preprocessing step for Naive Bayes?

a: Adding new random words to the text Explanation

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b: Removing stopwords such as 'the', 'is', and 'in' Explanation

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c: Encrypting the entire text Explanation

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d: Translating the text into another language Explanation

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What does a classifier do in machine learning?

a: It stores and retrieves data Explanation

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b: It assigns labels to input data based on learned patterns Explanation

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c: It generates random datasets Explanation

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d: It sorts values in ascending order Explanation

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