CountVectorizer().fit_transform() 是否保留输入顺序？

Question

I'm wondering if, when I use CountVectorizer().fit_transform() , the output preserves the order of the input.

My input is a list of documents. I know that the output matches the input in terms of the length, but I'm not sure if they are ordered the same way.

I understand that I might not be explaining it very well, so here's an example.

Say if I have:

input = ["<text_1>", "<text_2>", "<text_3>"]
a = CountVectorizer().fit_transform(input)

Will the indexes correspond as though order is preserved?

For example, in:

  (0, 33)   1
...
  (0, 42)   8
...
  (385, 58) 1
  (385, 51) 6

Is (0, 33) 1 eqivalent to input[0] , or (385, 58) 1 to input[365] ?

Answer 1

Yes, the row order is preserved. This must be true for all scikit-learn transformation methods, because a common workflow is to split your data into a feature matrix X and a target vector y , where each row of the matrix corresponds to one element of the vector. When you transform X , you must still be able to train the model on the transformed X paired with y , so the order must be preserved.