Semi-supervised Clustering Based on K-Nearest Neighbors
Horng-Lin Shieh · 2012
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.