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c-TF-IDF

ML Models & Algorithms
Class-based Term Frequency-Inverse Document Frequency; used by BERTopic for clearer topic representation and selection of important terms per cluster.

c-TF-IDF stands for Class-based Term Frequency-Inverse Document Frequency. It is a key component of the BERTopic algorithm.
This weighting scheme is used to refine the clusters created by HDBSCAN. Unlike models like Top2Vec, which rely mainly on semantic embeddings, BERTopic uses c-TF-IDF to highlight the most representative words for each topic. This results in clear topic words and yielding easily interpretable topics, giving BERTopic richer modeling capabilities.

Related Concepts

TF-IDF with Cosine Similarity TF-IDF (Term Frequency-Inverse Document Frequency) N-gram Matching Entity Extraction (NER) Lexical or morphological analysis

Sources & References

Introduction to Machine Learning for SEOs Course
academy.mlforseo.com

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