Browsing by Author "Györfi, László"
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- ItemDetecting ineffective features for pattern recognition(Oberwolfach : Mathematisches Forschungsinstitut Oberwolfach, 2017) Györfi, László; Walk, HarroFor a binary classification problem, the hypothesis testing is studied, that a component of the observation vector is not effective, i.e., that component carries no information for the classification. We introduce nearest neighbor and partitioning estimates of the Bayes error probability, which result in a strongly consistent test.
- ItemExact rate of convergence of k-nearest-neighbor classification rule(Oberwolfach : Mathematisches Forschungsinstitut Oberwolfach, 2017) Györfi, László; Döring, Maik; Walk, HarroA binary classification problem is considered. The excess error probability of the k-nearest neighbor classification rule according to the error probability of the Bayes decision is revisited by a decomposition of the excess error probability into approximation and estimation error. Under a weak margin condition and under a modified Lipschitz condition, tight upper bounds are presented such that one avoids the condition that the feature vector is bounded.