Virtual Labs

a: By calculating the prior probability of each class b: By calculating the likelihood probability of each word given each class c: By combining the prior and likelihood probabilities using Bayes' theorem d: By using gradient descent to optimize the model parameters

What is the purpose of Laplace smoothing in Naive Bayes text classification?

a: To handle class imbalance in the dataset b: To handle missing values in the dataset c: To handle zero probabilities for unseen words d: To handle outliers in the dataset

In the context of text classification using Naive Bayes, what does the term 'bag-of-words' refer to?

a: A representation of text data as a collection of unordered words b: A representation of text data as a sequence of words c: A method for weighting words based on their frequency in documents d: A technique for reducing the dimensionality of text data

Which of the following is NOT a common text classification task?

a: Document categorization b: Sentiment analysis c: Spam email detection d: Image recognition

In text classification, what is the goal?

a: To extract information from images b: To categorize text documents into predefined classes or categories c: To perform sentiment analysis on numerical data d: To generate text summaries from audio files

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