Clustering and pattern classification
Document Type
Syllabus
Publication Date
1-1-2008
Abstract
Clustering is a method to arrange data points into groups or clusters based on a predefined similarity criterion. Classification maps the data points or their representative features into predefined classes to help the interpretation of the input data. There are several methods available for clustering and classification for computeraided diagnostic or decision making systems for medical applications. This chapter reviews some of the clustering and classification methods using deterministic as well as fuzzy approaches for data analysis.
Identifier
84969632484 (Scopus)
ISBN
[9789812705341, 9789812814807]
Publication Title
Principles and Advanced Methods in Medical Imaging and Image Analysis
External Full Text Location
https://doi.org/10.1142/9789812814807_0010
First Page
229
Last Page
266
Recommended Citation
Dhawan, Atam P. and Dai, Shuangshuang, "Clustering and pattern classification" (2008). Faculty Publications. 12977.
https://digitalcommons.njit.edu/fac_pubs/12977
