What is the primary disadvantage of using n-gram models for language modeling?<br /> A. a. High computational complexity <br />B. b. Inability to handle long-range dependencies <br />C. c. Overfitting to the training data <br />D. d. Lack of interpretability
Question
What is the primary disadvantage of using n-gram models for language modeling?<br /> A. a. High computational complexity <br />B. b. Inability to handle long-range dependencies <br />C. c. Overfitting to the training data <br />D. d. Lack of interpretability
Solution
The primary disadvantage of using n-gram models for language modeling is B. Inability to handle long-range dependencies.
N-gram models are based on the Markov assumption, which assumes that the probability of a word only depends on a few previous words. This assumption simplifies the model and makes it computationally efficient, but it also limits the model's ability to capture long-range dependencies between words. For example, in a sentence where the meaning of a word depends on a word much earlier in the sentence, an n-gram model might not be able to accurately predict the word.
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