Topological map for binary data

We propose a new algorithm using topological map on binary data. The usual Euclidean distance is replaced by binary distance measures, which take into account possible asymmetries of binary data. The method is illustrated on an example taken from literature. Finally an application from chemistry is presented. We show the eficiency of the proposed method when applied to high-dimensinal binary data.