{
  "id": "cond-mat/9803316",
  "version": "v2",
  "published": "1998-03-26T04:03:46.000Z",
  "updated": "1999-02-25T18:40:45.000Z",
  "title": "Statistical Mechanics of Learning in the Presence of Outliers",
  "authors": [
    "Rainer Dietrich",
    "Manfred Opper"
  ],
  "comment": "24 pages, 7 figures (minor extensions added)",
  "journal": "J. Phys. A: Math. Gen. 31 (1998) 9131-9147",
  "doi": "10.1088/0305-4470/31/46/005",
  "categories": [
    "cond-mat.dis-nn"
  ],
  "abstract": "Using methods of statistical mechanics, we analyse the effect of outliers on the supervised learning of a classification problem. The learning strategy aims at selecting informative examples and discarding outliers. We compare two algorithms which perform the selection either in a soft or a hard way. When the fraction of outliers grows large, the estimation errors undergo a first order phase transition.",
  "revisions": [
    {
      "version": "v2",
      "updated": "1999-02-25T18:40:45.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "statistical mechanics",
      "first order phase transition",
      "outliers grows large",
      "estimation errors undergo",
      "hard way"
    ],
    "tags": [
      "journal article"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 24,
      "language": "en",
      "license": "arXiv",
      "status": "editable"
    }
  }
}