STUDY OBJECTIVES To examine the internal validity of a dietary pattern analysis and its ability to discriminate clusters of people with similar dietary patterns using independently assessed nutrient intakes and heart disease risk factors. DESIGN AND PARTICIPANTS Population based study characterising dietary patterns using cluster analysis applied to data from the semiquantitative Framingham f...

The purpose of this study was to compare the assessment of caries patterns by clinical definition and by cluster analysis. One of five etiology-oriented caries patterns was assigned to Head Start children in primary dentition. Cluster analysis grouped children based on carious tooth surfaces for each child. One hundred twenty-seven of the 155 children with at least one carious lesion fell into ...

The objective of this paper is to describe some pattern recognition approaches for image segmentation. First, in the introduction, we present the general aspects of omogenity and texture recognition. Then we provide a mean-based feature extraction approach for uniformity analysis and a moment-based one for texture analysis. In the classification stage we propose both supervised and also unsuper...

In this paper, a cluster validity measure is presented to infer the appropriateness of data partitions. The proposed validity measure adopts a novel non-metric distance measure based on the idea of "point symmetry". The proposed validity measure can be applied in finding the number of clusters of different geometrical structures. The performance evaluation of the validity measure compares favor...

The continuing neuroscience advances, catalysed by multidisciplinary collaborations between the biological, computational, physical and chemical areas, have implied in increasingly more complex approaches to understand and model the mammals nervous systems. One particularly important related issue regards the investigation of the relationship between morphology and function of neuronal cells, w...

The objective of the present paper is to describe a pattern recognition approach for image segmentation. First, in the introduction, we describe the general aspects of uniformity and texture recognition. Then we provide a mean-based feature extraction approach for uniformity analysis and a moment-based one for texture analysis. In the classification stage we propose both supervised and also uns...

Fuzzy partitional clustering algorithms are widely used in pattern recognition field. Until now, more and more research results on them have been developed in the literature. In order to study these algorithms systematically and deeply, they are reviewed in this paper based on c-means algorithm, from metrics, entropy, and constraints on membership function or cluster centers. Moreover, the adva...

Data clustering is a process of arranging similar data into groups. Data clustering is a common technique for data analysis and is used in many fields, including data mining, pattern recognition and image analysis. In this paper a hybrid clustering algorithm based on K-mean is described. K-means clustering is a common and simple approach for data clustering but this method has some limitation s...