Properties of bagged nearest neighbour classifiers
β Scribed by Peter Hall; Richard J. Samworth
- Book ID
- 111038894
- Publisher
- Blackwell Publishing
- Year
- 2005
- Tongue
- English
- Weight
- 290 KB
- Volume
- 67
- Category
- Article
- ISSN
- 0952-8385
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
A novel classi"er is introduced to overcome the limitations of the k-NN classi"cation systems. It estimates the posterior class probabilities using a local Parzen window estimation with the k-nearest-neighbour prototypes (in the Euclidean sense) to the pattern to classify. A learning algorithm is al
It is now well-established that k nearest-neighbour classi"ers o!er a quick and reliable method of data classi"cation. In this paper we extend the basic de"nition of the standard k nearest-neighbour algorithm to include the ability to resolve con#icts when the highest number of nearest neighbours ar