4. Distance- and neighborhood-based methods
Here, we examine a first family of intuitive, high-performance methods based on the notion of distance between shapes. We successively study a classification method and a partitioning method, both based on this idea.
Among the multitude of RDF methods, the nearest-neighbor classification method and its immediate extension, the K-nearest-neighbor method, hold a special place. They are both natural and justified by certain theoretical results. We first describe the principle behind them, and then describe some of their properties.
Finally, we take a look at the partitioning framework and describe a common partitioning method based on the notion of distance, the K-means algorithm.
4.1 Classification by nearest neighbor
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Distance- and neighborhood-based methods
Global approaches to classification
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