Atlas · GenAI 2026
TF-IDF
Representing text with sparse term weights that combine within-document frequency and inverse document frequency, including vocabulary fitting, smoothing and vector normalization.
Also searchable as: TFIDF, TF IDF, Term Frequency–Inverse Document Frequency
conceptNLP FoundationsAI consensus: 0/3
Prerequisites
- mediumTokenization
Term units must be defined before frequency weighting.
Recommended reference
scikit-learn: Tf–idf term weighting — https://scikit-learn.org/stable/modules/feature_extraction.html#tfidf-term-weighting
Reviewed sources
Primary and first-party material reviewed for this editorial summary. These citations are separate from the AI consensus score above.
- scikit-learn: Tf–idf term weighting
Term-frequency and inverse-document-frequency weighting and sparse text representations.
- scikit-learn: TfidfVectorizer
Vocabulary construction and TF-IDF text-feature extraction.
- scikit-learn: TfidfTransformer
Weighting a supplied term-count matrix with IDF and normalization.
Notes from AI deep research
Related skills
- → is subcategory of: NLP