{
  "id": "0902.4389",
  "version": "v1",
  "published": "2009-02-25T15:14:31.000Z",
  "updated": "2009-02-25T15:14:31.000Z",
  "title": "Dimension reduction in representation of the data",
  "authors": [
    "A. G. Ramm"
  ],
  "categories": [
    "stat.ML",
    "math.NA",
    "math.ST",
    "stat.TH"
  ],
  "abstract": "Suppose the data consist of a set $S$ of points $x_j$, $1\\leq j \\leq J$, distributed in a bounded domain $D\\subset R^N$, where $N$ is a large number. An algorithm is given for finding the sets $L_k$ of dimension $k\\ll N$, $k=1,2,...K$, in a neighborhood of which maximal amount of points $x_j\\in S$ lie. The algorithm is different from PCA (principal component analysis)",
  "revisions": [
    {
      "version": "v1",
      "updated": "2009-02-25T15:14:31.000Z"
    }
  ],
  "analyses": {
    "subjects": [
      "62H35"
    ],
    "keywords": [
      "dimension reduction",
      "representation",
      "principal component analysis",
      "data consist",
      "large number"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 0,
      "language": "en",
      "license": "arXiv",
      "status": "editable",
      "adsabs": "2009arXiv0902.4389R"
    }
  }
}