Description

This database contains 279 attributes, 206 of which are linear valued and the rest are nominal. Concerning the study of H. Altay Guvenir: "The aim is to distinguish between the presence and absence of cardiac arrhythmia and to classify it in one of the 16 groups. Class 01 refers to 'normal' ECG classes 02 to 15 refers to different classes of arrhythmia and class 16 refers to the rest of unclassified ones. For the time being, there exists a computer program that makes such a classification. However there are differences between the cardiolog's and the programs classification. Taking the cardiolog's as a gold standard we aim to minimise this difference by means of machine learning tools." The names and id numbers of the patients were recently removed from the database.

Related Papers

  • Gisele L. Pappa and Alex Alves Freitas and Celso A A Kaestner. AMultiobjective Genetic Algorithm for Attribute Selection. Computing Laboratory Pontificia Universidade Catolica do Parana University of Kent at Canterbury. [link]
  • Krista Lagus and Esa Alhoniemi and Jeremias Seppa and Antti Honkela and Arno Wagner. INDEPENDENT VARIABLE GROUP ANALYSIS IN LEARNING COMPACT REPRESENTATIONS FOR DATA. Neural Networks Research Centre, Helsinki University of Technology. [link]
  • Shay Cohen and Eytan Ruppin and Gideon Dror. Feature Selection Based on the Shapley Value. School of Computer Sciences Tel-Aviv University. [link]
  • [link]

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