A comparative study of codification techniques for clustering Heart Disease database

This paper compares different proposals for codifying categorical attributes in a Heart Disease database, in order to be able to apply numerical clustering algorithms to them. The main idea of the new approach is a codification of categorical attributes based on polar coordinates. This will be compared with other methods for clustering mixed databases found in literature. This proposal has many advantages: it relatively easy to understand and apply, the increment in the length of the input matrix is not excessively large, and the committed error is under control. The proposed codification has been combined in this case with the well known K-means algorithm and has showed a very good performance in a Heart Disease database benchmark.