ManiSonS: A New Visualization Tool for Manifold Clustering.
José M. Martínez-Martínez, Pablo Escandell-Montero, José D. Martín‐Guerrero, Joan Vila‐Francés, Emilio Soria‐Olivas · The European Symposium on Artificial Neural Networks · 2013
M anifold learning is an important theme in machine learning. This paper proposes a new visualization approach to manifold clustering. The method is based on pie charts in order to obtain meaningful visu- alizations of the clustering results when applying a manifold technique. In addition to this, the proposed approach extracts all the existing rela- tionships among the attributes of the di! erent clusters and find the most important variables of the manifold in order to distinguish among the dif- ferent clusters. The methodology is tested in one synthetic data set and one real data set. Achieved results show the suitability and usefulness of the proposed approach.