Estimation of high-density regions using one-class neighbor machines

@article{Muoz2006EstimationOH,
  title={Estimation of high-density regions using one-class neighbor machines},
  author={Alberto Mu{\~n}oz and Javier M. Moguerza},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year={2006},
  volume={28},
  pages={476-480}
}
In this paper, we investigate the problem of estimating high-density regions from univariate or multivariate data samples. We estimate minimum volume sets, whose probability is specified in advance, known in the literature as density contour clusters. This problem is strongly related to one-class support vector machines (OCSVM). We propose a new method to solve this problem, the one-class neighbor machine (OCNM) and we show its properties. In particular, the OCNM solution asymptotically… CONTINUE READING
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