Imagine that you built a bag of words model for a corpus containing a large number...

 

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Imagine that you built a bag of words model for a corpus containing a large number of documents (> 5), and encoded the top five words in a matrix, using the sorting metrics described in the video. If the top five words were: {"cat": 150, "dog": 187, "rabbit": 101, "mouse": 101,"snake": 43} And the first five rows in the matrix of raw frequencies is: 10 5 0 3 2 0 4 7 2 1 8 6 3 1 0 5 8 9 4 3 12 0 1 2 4, What was the count of the word "cat" in document 0? What was the count of the word "mouse" in document 2? Imagine that you built a bag of words model for a corpus containing a large number of documents (> 5), and encoded the top five words in a matrix, using the sorting metrics described in the video. If the top five words were: {"cat": 150, "dog": 187, "rabbit": 101, "mouse": 101,"snake": 43} And the first five rows in the matrix of raw frequencies is: 10 5 0 3 2 0 4 7 2 1 8 6 3 1 0 5 8 9 4 3 12 0 1 2 4, What was the count of the word "cat" in document 0? What was the count of the word "mouse" in document 2? Imagine that you built a bag of words model for a corpus containing a large number of documents (> 5), and encoded the top five words in a matrix, using the sorting metrics described in the video. If the top five words were: {"cat": 150, "dog": 187, "rabbit": 101, "mouse": 101,"snake": 43} And the first five rows in the matrix of raw frequencies is: 10 5 0 3 2 0 4 7 2 1 8 6 3 1 0 5 8 9 4 3 12 0 1 2 4, What was the count of the word "cat" in document 0? What was the count of the word "mouse" in document 2?

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