Nearest centroid classifier

In machine learning, a nearest centroid classifier or nearest prototype classifier is a classification model that assigns to observations the label of the class of training samples whose mean (centroid) is closest to the observation.

When applied to text classification using tf*idf vectors to represent documents, the nearest centroid classifier is known as the Rocchio classifier because of its similarity to the Rocchio algorithm for relevance feedback.[1]

An extended version of the nearest centroid classifier has found applications in the medical domain, specifically classification of tumors.[2]


  • Training procedure: given labeled training samples with class labels , compute the per-class centroids where is the set of indices of samples belonging to class .
  • Prediction function: the class assigned to an observation is .

See also


  1. Manning, Christopher; Raghavan, Prabhakar; Schütze, Hinrich (2008). "Vector space classification". Introduction to Information Retrieval. Cambridge University Press.
  2. Tibshirani, Robert; Hastie, Trevor; Narasimhan, Balasubramanian; Chu, Gilbert (2002). "Diagnosis of multiple cancer types by shrunken centroids of gene expression". Proceedings of the National Academy of Sciences. 99 (10): 6567–6572. doi:10.1073/pnas.082099299. PMC 124443. PMID 12011421.
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