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What is the purpose of using a Multinomial distribution in text data modeling?
What is the purpose of using a Multinomial distribution in text data modeling?
- To handle a single event out of K possibilities (correct)
- To model the outcome of multiple events simultaneously
- To predict the occurrence of rare words in text data
- To estimate probabilities for each word in the vocabulary
In the context of text data, what does 'N-Grams' refer to?
In the context of text data, what does 'N-Grams' refer to?
- Models that estimate word co-occurrence frequencies
- Conditional probabilities based on word sequences (correct)
- Grammatical errors in the text
- A type of Google autocompletion
How is the vocabulary size represented in text data modeling using the Multinomial distribution?
How is the vocabulary size represented in text data modeling using the Multinomial distribution?
- As the number of unique words in the dataset (correct)
- As the total number of words in a document
- By the number of documents in the corpus
- By the frequency of rare words in the text
What is the maximum likelihood solution when using the Multinomial distribution for text data modeling?
What is the maximum likelihood solution when using the Multinomial distribution for text data modeling?
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Why are Conditional Probabilities important in language modelling with N-Grams?
Why are Conditional Probabilities important in language modelling with N-Grams?
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