• Detecting Ineffective Features for Pattern Recognition 

      [OWP-2017-26] Györfi, László; Walk, Harro (Mathematisches Forschungsinstitut Oberwolfach, 2017-10-17)
      For 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 ...
    • Exact Rate of Convergence of k-Nearest-Neighbor Classification Rule 

      [OWP-2017-25] Györfi, László; Döring, Maik; Walk, Harro (Mathematisches Forschungsinstitut Oberwolfach, 2017-10-16)
      A 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 ...
    • Rate of Convergence of the Density Estimation of Regression Residual 

      [OWP-2012-08] Györfi, László; Walk, Harro (Mathematisches Forschungsinstitut Oberwolfach, 2012)
      Consider the regression problem with a response variable $Y$ and with a $d$-dimensional feature vector $X$. For the regression function $m(x) = \mathbb{E}\{Y|X = x\}$, this paper investigates methods for estimating the ...
    • Strongly Consistent Density Estimation of Regression Redidual 

      [OWP-2012-07] Györfi, László; Walk, Harro (Mathematisches Forschungsinstitut Oberwolfach, 2012)
      Consider the regression problem with a response variable $Y$ and with a $d$-dimensional feature vector $X$. For the regression function $m(x) = \mathbb{E}\{Y|X = x\}$, this paper investigates methods for estimating the ...