Fast reciprocal nearest neighbors clustering
| Autor: | Roberto J. López-Sastre, Saturnino Maldonado-Bascón, P. Gil-Jimenez, Daniel Oñoro-Rubio |
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| Rok vydání: | 2012 |
| Předmět: |
Computer Science::Neural and Evolutionary Computation
Correlation clustering Data structure computer.software_genre k-nearest neighbors algorithm Control and Systems Engineering Nearest-neighbor chain algorithm Signal Processing Canopy clustering algorithm Computer Vision and Pattern Recognition Data mining Electrical and Electronic Engineering Cluster analysis Projection (set theory) Algorithm computer Software Reciprocal Mathematics |
| Zdroj: | Signal Processing. 92:270-275 |
| ISSN: | 0165-1684 |
| Popis: | This paper presents a novel approach for accelerating the popular reciprocal nearest neighbors (RNN) clustering algorithm, i.e. the fast-RNN. We speed up the nearest neighbor chains construction via a novel dynamic slicing strategy for the projection search paradigm. We detail an efficient implementation of the clustering algorithm along with a novel data structure, and present extensive experimental results that illustrate the excellent performance of fast-RNN in low- and high-dimensional spaces. A C++ implementation has been made publicly available. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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