TF-IDF: Difference between revisions
From Algolit
Sarahgarcin (talk | contribs) (Created page with "The TF-IDF (Term Frequency-Inverse Document Frequency) is a weighting method used in text search. This statistical measure makes it possible to evaluate the importance of a te...") |
|||
| Line 2: | Line 2: | ||
A web based-interface shows this algorithm through animations allowing to understand the different steps of text classification. How does a TF-IDF-based program read a text? How does it transform words into numbers? | A web based-interface shows this algorithm through animations allowing to understand the different steps of text classification. How does a TF-IDF-based program read a text? How does it transform words into numbers? | ||
| + | |||
| + | |||
| + | [[Category:Data_Workers]][[Category:Data_Workers_EN]] | ||
Revision as of 13:51, 28 February 2019
The TF-IDF (Term Frequency-Inverse Document Frequency) is a weighting method used in text search. This statistical measure makes it possible to evaluate the importance of a term contained in a document, relative to a collection or corpus. The weight increases in proportion to the number of occurrences of the word in the document. It also varies according to the frequency of the word in the corpus. The TF-IDF is used in particular in the classification of spam in email softwares.
A web based-interface shows this algorithm through animations allowing to understand the different steps of text classification. How does a TF-IDF-based program read a text? How does it transform words into numbers?