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008			000807s1984 caua obs 000 0 eng d
020			_a0585180873 _q(electronic bk.)
020			_a9780585180878 _q(electronic bk.)
020			_a9781412983648 _q(electronic bk.)
020			_a1412983649 _q(electronic bk.)
020			_z0803923767 _q(pbk.)
020			_z9780803923768 _q(pbk.)
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082	0	4	_a519.5/35 _219
100	1		_aAldenderfer, Mark S. _929266 _eσυγγραφέας.
245	1	0	_aCluster analysis / _cMark S. Aldenderfer, Roger K. Blashfield.
260			_aBeverly Hills : _bSage Publications, _c1984.
300			_a1 ηλεκτρονική πηγή (88 σ.) : _bεικ.
490	1		_aSage university papers series. Quantitative applications in the social sciences ; _vno. 07-044
504			_aΠεριλαμβάνει βιβλιογραφικές παραπομπές (σ. 84-87).
505	0		_a1. Introduction. How clustering methods are used -- Data sets to be used as examples -- A few cautions about cluster analysis -- 2. Similarity measures. Terminology -- The concept of similarity -- The choice of variables -- Similarity measures -- 3. A review of clustering methods. On the nature of clusters -- Hierarchical agglomerative methods -- Iterative partitioning methods -- Factor analysis variants -- Other methods -- Determining the number of clusters -- Comparing clustering methods -- 4. Validation techniques. Cophenetic correlation -- Significance tests on variables used to create clusters -- Replication -- Significance tests on external variables -- Monte Carlo procedures -- 5. Cluster analysis software and the literature on clustering -- Collections of subroutines and algorithms -- Statistical packages containing clustering software -- Cluster analysis packages -- Simple cluster analysis programs -- The literature on cluster analysis -- Guide to reporting cluster analysis studies -- Appendix. Example data sets (burial data) -- Notes -- References -- About the authors.
506			_3Αντίτυπο για χρήση _fΜη καθορισμένοι περιορισμοί _2star _5MiAaHDL
520			_aThis book is designed to be an introduction to cluster analysis for those with no background and for those who need an up-to-date and systematic guide through the maze of concepts, techniques, and algorithms associated with the clustering data. The authors begin by discussing measures of similarity, the input needed to perform any clustering analysis. They note varying theoretical meanings of the concept and discuss the set of empirical measures most commonly used to measure similarity. Various methods for actually identifying the clusters are then described. Finally, they discuss procedures for validating the adequacy of a cluster analysis. At all points, the differing concepts and techniques are compared and evaluated.
533			_aΗλεκτρονική αναπαραγωγή. _b[Χ.τ.] : _cHathiTrust Digital Library, _d2010.
583	1		_aψηφιοποιημένο _c2010 _hHathiTrust Digital Library _lcommitted to preserve _2pda _5MiAaHDL
650	1	4	_aΚοινωνικές επιστήμες _xΣτατιστικές μέθοδοι _9692
650	1	4	_aΣυσταδοποίηση _9129380
655		0	_aΗλεκτρονικά βιβλία
700	1		_aBlashfield, Roger K., _d1944- _9184956 _eσυγγραφέας.
830		0	_aQuantitative applications in the social sciences _vno. 07-044. _9165029
856	4	0	_uhttp://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=24703
942			_2ddc _cERS
998			_cΓκόγκου _d12-2020