Neural Networks for Clustering Analysis of Molecular Data

In this paper hierarchical cluster and the competitive learning cluster are compared by using molecular data of large size sets. We construct a reproducible matrix to evaluate the quality of clustering, and dead nodes problem of the competitive learning network is solved by the conscience mechanism. The experimental results show that the hierarchical clustering can represent a multi-level hierarchy which show the tree relation of cluster distance, the competitive learning network has a good clustering reproducible and indicate the effectiveness of clusters for molecular data