Minimum expected risk probability estimates for nonparametric neighborhood classifiers
M. Gupta, Luca Cazzanti, Santosh Kumar Srivastava · IEEE/SP 13th Workshop on Statistical Signal Processing, 2005 · 2005
We consider the problem of estimating class probabilities for a given feature vector using nonparametric neighborhood methods, such as k-nearest neighbors (k-NN). This paper's contribution is the application of minimum expected risk estimates for neighborhood learning methods, an analytic formula for the minimum expected risk estimate for weighted k-NN classifiers, and examples showing that the difference can be significant