Created | Fri, 19 Apr 2013 17:53:08 +0000 |
Published | Fri, 19 Apr 2013 18:40:32 +0000 |
Algorithm | BigML Memory Tree |
Split criterion | |
Support threshold | |
Depth threshold | 512 |
Node threshold | 512 |
Missing splits | No |
Statistical pruning | Smart pruning |
The aim is to distinguish between the presence and absence of cardiac arrhythmia and to classify it in one of the 16 groups:
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.
Source
Arrhythmia Data Set at UCI Machine Learning Repository