Arrhythmia
Abstract
Distinguish between the presence and absence of cardiac arrhythmia and classify it in one of the 16 groups.
Purpose
Additional Information 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.
| Name | Role | Type | Description | Missing |
|---|---|---|---|---|
| Variable 1 | Feature | Integer | - | No |
| Variable 2 | Feature | Integer | - | No |
| Variable 3 | Feature | Integer | - | No |
| Variable 4 | Feature | Integer | - | No |
| Variable 5 | Feature | Integer | - | No |
| Variable 6 | Feature | Integer | - | No |
| Variable 7 | Feature | Integer | - | No |
| Variable 8 | Feature | Integer | - | No |
| Variable 9 | Feature | Integer | - | No |
| Variable 10 | Feature | Integer | - | No |
Papers Citing this Dataset
19 papers found
Privacy Preserving Similarity Measurement
By Zhang Guo-rong.
Mining Complex, Maximal and Complete Sub-graphs and Sets of Correlated Variables with Applications to Feature Subset Selection
By Florian Verhein.
Feature Selection via Coalitional Game Theory
By Shay Cohen, Gideon Dror, Eytan Ruppin.
Achieving Privacy Preservation When Sharing Data for Clustering
By Stanley Oliveira, Osmar ZaĂŻane.