Semi-supervised Clustering Based on K-Nearest Neighbors

In this study, a semi-supervised clustering algorithm, based on k-nearest neighbors (k-NN), is proposed. The distance relationships between unlabeled and k-nearest neighbor data of each cluster are adopted in order to categorize the unlabeled data. Experiment result shows that proposed method can obtain a good performance.

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