New model-based estimators of the uncertainty of pixel-level and areal k-nearest neighbour (k nn ) predictions of attribute Y from remotely-sensed ancillary data X are presented. Non-parametric functions predict Y from scalar 'Single Index Model' transformations of X. Variance functions generated es
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Model-based prediction error uncertainty estimation for k-nn method
โ Scribed by Hyon-Jung Kim; Erkki Tomppo
- Book ID
- 108261220
- Publisher
- Elsevier Science
- Year
- 2006
- Tongue
- English
- Weight
- 343 KB
- Volume
- 104
- Category
- Article
- ISSN
- 0034-4257
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The nearest neighbor rule or k-nearest neighbor rule is a technique of nonparametric pattern recognition. Its algorithm is simple and the error is smaller than twice the Bayes error if there are enough training samples. However, it requires an enormous amount of computation, proportional to the numb