  A new model called Clustering with Neural Network and Index (CNNI) is
introduced. CNNI uses a Neural Network to cluster data points. Training of the
Neural Network mimics supervised learning, with an internal clustering
evaluation index acting as the loss function. An experiment is conducted to
test the feasibility of the new model, and compared with results of other
clustering models like K-means and Gaussian Mixture Model (GMM). The result
shows CNNI can work properly for clustering data; CNNI equipped with MMJ-SC,
achieves the first parametric (inductive) clustering model that can deal with
non-convex shaped (non-flat geometry) data.
