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nearest centroid classifier : ウィキペディア英語版
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.
An extended version of the nearest centroid classifier has found applications in the medical domain, specifically classification of tumors.
== Algorithm ==

* Training procedure: given labeled training samples \textstyle\_n, y_n)\} with class labels y_i \in \mathbf, compute the per-class centroids \textstyle\vec = \frac\underset \vec_i where C_l is the set of indices of samples belonging to class l \in \mathbf.
* Prediction function: the class assigned to an observation \vec is \hat = __l - \vec\|.

抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
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