Abstract :
The concept of "neighborhood of a point" has been used in various programs for analyzing spatial dot patterns. The common definition based on k-nearest neighbors does not reflect the intuitive cluster associations of certain points in simple patterns. An alternative definition is proposed to reflect such associations more satisfactorily. Its applications includes cluster analysis and descriptive measures for dot patterns.
Keywords :
Clustering, descriptive measures, dot patterns, point neighborhood, spatial analysis.; Algorithms; Classification tree analysis; Error correction; Error correction codes; Frequency; Image coding; Nearest neighbor searches; Pattern analysis; Pattern recognition; Program processors; Clustering, descriptive measures, dot patterns, point neighborhood, spatial analysis.;
