{
  "id": "1301.6944",
  "version": "v1",
  "published": "2013-01-29T15:09:56.000Z",
  "updated": "2013-01-29T15:09:56.000Z",
  "title": "On the Consistency of the Bootstrap Approach for Support Vector Machines and Related Kernel Based Methods",
  "authors": [
    "Andreas Christmann",
    "Robert Hable"
  ],
  "comment": "13 pages",
  "categories": [
    "stat.ML",
    "cs.LG"
  ],
  "abstract": "It is shown that bootstrap approximations of support vector machines (SVMs) based on a general convex and smooth loss function and on a general kernel are consistent. This result is useful to approximate the unknown finite sample distribution of SVMs by the bootstrap approach.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2013-01-29T15:09:56.000Z"
    }
  ],
  "analyses": {
    "subjects": [
      "62G08",
      "62G09",
      "62G20",
      "62G86"
    ],
    "keywords": [
      "support vector machines",
      "bootstrap approach",
      "related kernel",
      "consistency",
      "unknown finite sample distribution"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 13,
      "language": "en",
      "license": "arXiv",
      "status": "editable",
      "adsabs": "2013arXiv1301.6944C"
    }
  }
}