An Information Function Approach to Dimensionality Analysis and Curved Manifold Clustering

作者: J.N. SRIVASTAVA

DOI: 10.1016/B978-0-12-426653-7.50031-4

关键词:

摘要: Publisher Summary This chapter focuses on an information function approach to dimensionality analysis and curved manifold clustering. The discusses the potentialities of a method through Monte Carlo studies. It entropy in discrete continuous cases explains how measure uncertainty connected with is under also presents applications some weaving techniques.

参考文章(13)
J. B. Kruskal, Nonmetric multidimensional scaling: A numerical method Psychometrika. ,vol. 29, pp. 115- 129 ,(1964) , 10.1007/BF02289694
A.P. Dempster, An overview of multivariate data analysis Journal of Multivariate Analysis. ,vol. 1, pp. 316- 346 ,(1971) , 10.1016/0047-259X(71)90006-6
Roger N. Shepard, Metric structures in ordinal data Journal of Mathematical Psychology. ,vol. 3, pp. 287- 315 ,(1966) , 10.1016/0022-2496(66)90017-4
D.K. Osborne, Further extensions of a theorem of dimensional analysis Journal of Mathematical Psychology. ,vol. 7, pp. 236- 242 ,(1970) , 10.1016/0022-2496(70)90046-5
Forrest W. Young, Nonmetric multidimensional scaling: Recovery of metric information Psychometrika. ,vol. 35, pp. 455- 473 ,(1970) , 10.1007/BF02291820
Enrique H. Ruspini, A new approach to clustering Information & Computation. ,vol. 15, pp. 22- 32 ,(1969) , 10.1016/S0019-9958(69)90591-9
M.A. Hamdan, Chris P. Tsokos, An information measure of association in contingency tables Information & Computation. ,vol. 19, pp. 174- 179 ,(1971) , 10.1016/S0019-9958(71)90799-6