Nearest centroid classifier

Rocchio Classification

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]

Algorithm

• 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

• Cluster hypothesis
• k-means clustering
• k-nearest neighbor algorithm
• Linear discriminant analysis

References

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). doi:10.1073/pnas.082099299.