Stability analysis in K-means clustering.
This paper develops a new procedure, called stability analysis, for K-means clustering. Instead of ignoring local optima and only considering the best solution found, this procedure takes advantage of additional information from a K-means cluster analysis. The information from the locally optimal solutions is collected in an object by object co-occurrence matrix. The co-occurrence matrix is clustered and subsequently reordered by a steepest ascent quadratic assignment procedure to aid visual interpretation of the multidimensional cluster structure. Subsequently, measures are developed to determine the overall structure of a data set, the number of clusters and the multidimensional relationships between the clusters.
Steinley
Douglas
D
Department of Psychological Sciences, 210 McAlester Hall, Columbia, MO 65211, USA. steinleyd@missouri.edu
D016000:Cluster Analysis; D006801:Humans; D008960:Models, Psychological; D011584:Psychology / Q000706:statistics & numerical data