An investigation into unsupervised clustering techniques
H.S. Lee, Nicholas H. Younan · 2002
The performance of several unsupervised clustering techniques is compared using two clearly separated 3-D data sets that are not separable by any hyperplane. The result shows that the self-organizing feature map can cluster data sets successfully without any prior information of given data while the k-means and the fuzzy k-means algorithm fail to cluster correctly.