Multidimensional Similarity Structure Analysis

@book{citeulike:2983580, abstract = {\_\_Multidimensional Similarity\_ \_Structure Analysis\_\_ comprises a class of models that represent similarity among entities (for example, variables, items, objects, persons, etc.) in multidimensional space to permit one to grasp more easily the interrelations and patterns present in the data. The book is oriented to both researchers who have little or no previous exposure to data scaling and have no more than a high school background in mathematics and to investigators who would like to extend their analyses in the direction of hypothesis and theory testing or to more intimately understand these analytic procedures. The book is repleted with examples and illustrations of the various techniques drawn largely, but not restrictively, from the social sciences, with a heavy emphasis on the concrete, geometric or spatial aspect of the data representations.}, author = {Borg, I. and Lingoes, J. }, citeulike-article-id = {2983580}, comment = {Introduced multidimensional scaling.}, edition = {1}, howpublished = {Hardcover}, isbn = {0387965254}, keywords = {dimensionality-reduction, machine-learning}, month = {July}, posted-at = {2008-07-10 04:12:22}, priority = {2}, publisher = {Springer}, title = {Multidimensional Similarity Structure Analysis}, url = {http://www.amazon.ca/exec/obidos/redirect?tag=citeulike09-20\&path=ASIN/0387965254}, year = {1987} }

TY - BOOK ID - citeulike:2983580 L3 - citeulike-article-id:2983580 TI - Multidimensional Similarity Structure Analysis PB - Springer SN - 0387965254 N2 - __Multidimensional Similarity_ _Structure Analysis__ comprises a class of models that represent similarity among entities (for example, variables, items, objects, persons, etc.) in multidimensional space to permit one to grasp more easily the interrelations and patterns present in the data. The book is oriented to both researchers who have little or no previous exposure to data scaling and have no more than a high school background in mathematics and to investigators who would like to extend their analyses in the direction of hypothesis and theory testing or to more intimately understand these analytic procedures. The book is repleted with examples and illustrations of the various techniques drawn largely, but not restrictively, from the social sciences, with a heavy emphasis on the concrete, geometric or spatial aspect of the data representations. KW - dimensionality-reduction KW - machine-learning N1 - Introduced multidimensional scaling. AU - Borg, I AU - Lingoes, J PY - 1987/07/02/ UR - http://www.amazon.ca/exec/obidos/redirect?tag=citeulike09-20&path=ASIN/0387965254 ER -