python--text Feature Extraction Countvectorize

countvectorize

From: Python Learning text feature extraction (ii) Countvectorizer tfidfvectorizer Chinese processing-CSDN Blog

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The commonly used data input form is: list, list element is the string representing the article, a string represents an article, the string is already split goodCountvectorizer is also available in Chinese

parameter Table	function
Stop_words	to deactivate a glossary; customize the Stop vocabulary
Token_pattern	filter rules;

property sheet	function
Vocabulary_	A glossary; a typical word.
Get_feature_names ()	Vocabulary of all text; list type
Stop_words_	Return to Inactive glossary

Countvectorizer is to convert the words in the text to the word frequency matrix by the Fit_transform function, and the matrix element A[i][j] to denote the word frequency of the J words under the I text. That is, the number of occurrences of each word, through get_feature_names () can see all the text of the keyword, through the toarray () can see the results of the word frequency matrix.

Method Table	function
Fit_transform (X)	Fit the model and return the text matrix

python--text Feature Extraction Countvectorize