Approximate Clustering Via the Mountain Method

We develop a simple and effective approach for approximate estimation of the cluster centers on the basis of the concept of a mountain function. We call the procedure the mountain method. It can be useful for obtaining the initial values of the clusters that are required by more complex cluster algorithms. It also can be used as a stand alone simple approximate clustering technique. The method is based upon a griding on the space, the construction of a mountain function from the data and then a destruction of the mountains to obtain the cluster centers. >