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Ideal bootstrap estimation of expected prediction error for k-nearest neighbor classifiers: Applications for classification and error assessment

โœ Scribed by Brian M. Steele; David A. Patterson


Book ID
110270480
Publisher
Springer US
Year
2000
Tongue
English
Weight
99 KB
Volume
10
Category
Article
ISSN
0960-3174

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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