{
  "id": "cond-mat/0010423",
  "version": "v1",
  "published": "2000-10-26T15:11:01.000Z",
  "updated": "2000-10-26T15:11:01.000Z",
  "title": "Hierarchical learning in polynomial Support Vector Machines",
  "authors": [
    "Sebastian Risau-Gusman",
    "Mirta B. Gordon"
  ],
  "comment": "22 pages, 7 figures, submitted to Machine Learning",
  "categories": [
    "cond-mat.dis-nn"
  ],
  "abstract": "We study the typical properties of polynomial Support Vector Machines within a Statistical Mechanics approach that allows us to analyze the effect of different normalizations of the features. If the normalization is adecuately chosen, there is a hierarchical learning of features of increasing order as a function of the training set size.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2000-10-26T15:11:01.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "polynomial support vector machines",
      "hierarchical learning",
      "statistical mechanics approach",
      "normalization",
      "typical properties"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 22,
      "language": "en",
      "license": "arXiv",
      "status": "editable",
      "adsabs": "2000cond.mat.10423R"
    }
  }
}