Integrated Dimensionality Reduction Technique for Mixed Data Involving Categorical Values

An extension to the recent dimensionality-reduction technique t-SNE is proposed. The extension facilitates t-SNE to handle mixed-type datasets. Each attribute of the data is associated with a distance hierarchy which allows the distance between numeric values and between categorical values be measured in a unified manner. More importantly, domain knowledge regarding semantic distance between categorical values can be specified in the hierarchy. Consequently, the extended t-SNE can reflect topological order of the high-dimensional, mixed data in the low-dimensional space.