@InProceedings{PetrikChudacekLhotska:MLSP2007,
  IS = { zkontrolovano 12 Dec 2007 },
  UPDATE  = { 2007-12-11 },
  author =      { Petr{\'\i}k, Milan and Chud{\'a}{\v c}ek, V{\'a}clav and Lhotsk{\'a}, Lenka },
  title =       { Generalization of rule-based decicion tree to fuzzy intervals for {ECG}-beat clustering },
  year =        { 2007 },
  pages =       { 205--210 },
  booktitle =   { MLSP-IEEE 2007: Machine Learning for Signal Processing XVII },
  publisher =   { IEEE Computer Society },
  address =     { Los Alamitos, USA },
  isbn =        { 1-4244-1566-7 },
  book_pages =  { 446 },
  month =       { August },
  day =         { 27--19 },
  venue =       { Thessaloniki, Greece },
  organization ={ IEEE },
  annote = { In this paper, we compare two approaches to clustering
    and diagnosis of the ECG heart beats. In the first approach, the
    Rule-Based Decision Tree method is presented; in this method the
    decision rules are based on classical intervals.  The second
    approach is based on fuzzification of the intervals; this accords
    with the situation when the knowledge described by books and
    cardiologists is vague or unclear. We discuss the way how the
    results of the fuzzy and the classical approaches can be
    compared. We choose the sensitivity and specificity as they are a
    well established measures in the field of the clinical
    medicine. We define a generalization of the sensitivity and
    specificity for fuzzy clusters in order to prove correctness of
    our presented fuzzy approach. },
  authorship =  { 34-33-33 },
  project =     { 1ET201210527, 13037D/06/A, GACR 201/07/1136 },
  www         = { http://mlsp2007.conwiz.dk/ },
}