L1 and L2 Approximation Clustering for Mixed Data: Scatter Decompositions and Algorithms

L1 and L2 Approximation Clustering for Mixed Data: Scatter Decompositions and Algorithms

Clustering is considered usually an art rather than a science because of lacking comprehensive mathematical theories in the discipline. The major issue raised in this paper is that L2 and L1 approximation bilinear clustering can provide a theoretical framework for an extensive part of partitioning a...

Ausführliche Beschreibung

Bibliographische Detailangaben
Veröffentlicht in:Lecture Notes-Monograph Series. - Institute of Mathematical Statistics, 1982. - 31(1997) vom: Jan., Seite 473-486
1. Verfasser: Mirkin, Boris (VerfasserIn)
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 1997
Zugriff auf das übergeordnete Werk:Lecture Notes-Monograph Series
Schlagworte:Partitioning Hierarchy Mixed data Approximation Contingency coefficients Mathematics Behavioral sciences Information science Applied sciences Philosophy
LEADER 01000caa a22002652 4500
001 JST055248489
003 DE-627
005 20240622004659.0
007 cr uuu---uuuuu
008 150324s1997 xx |||||o 00| ||eng c
035 |a (DE-627)JST055248489 
035 |a (JST)4355999 
040 |a DE-627  |b ger  |c DE-627  |e rakwb 
041 |a eng 
084 |a 62H30  |2 MSC 
084 |a 90C27  |2 MSC 
084 |a 05C50  |2 MSC 
084 |a 05C05  |2 MSC 
100 1 |a Mirkin, Boris  |e verfasserin  |4 aut 
245 1 0 |a L1 and L2 Approximation Clustering for Mixed Data: Scatter Decompositions and Algorithms 
264 1 |c 1997 
336 |a Text  |b txt  |2 rdacontent 
337 |a Computermedien  |b c  |2 rdamedia 
338 |a Online-Ressource  |b cr  |2 rdacarrier 
520 |a Clustering is considered usually an art rather than a science because of lacking comprehensive mathematical theories in the discipline. The major issue raised in this paper is that L2 and L1 approximation bilinear clustering can provide a theoretical framework for an extensive part of partitioning and hierarchic clustering concerning its algorithmical and interpretational aspects, which is supported with a theoretical evidence. 
540 |a Copyright 1997 Institute of Mathematical Statistics 
650 4 |a Partitioning 
650 4 |a Hierarchy 
650 4 |a Mixed data 
650 4 |a Approximation 
650 4 |a Contingency coefficients 
650 4 |a Mathematics  |x Mathematical procedures  |x Approximation 
650 4 |a Mathematics  |x Pure mathematics  |x Linear algebra  |x Vector analysis  |x Mathematical vectors 
650 4 |a Behavioral sciences  |x Psychology  |x Cognitive psychology  |x Cognitive processes  |x Comprehension  |x Information processing  |x Standardization 
650 4 |a Mathematics  |x Applied mathematics  |x Statistics  |x Applied statistics  |x Descriptive statistics  |x Central tendencies  |x Statistical median 
650 4 |a Information science  |x Information analysis  |x Data analysis  |x Data reduction  |x Cluster analysis 
650 4 |a Mathematics  |x Applied mathematics  |x Statistics  |x Applied statistics  |x Statistical models  |x Parametric models 
650 4 |a Mathematics  |x Pure mathematics  |x Linear algebra  |x Matrix theory  |x Matrices 
650 4 |a Applied sciences  |x Computer science  |x Artificial intelligence  |x Machine learning 
650 4 |a Applied sciences  |x Research methods  |x Modeling 
650 4 |a Philosophy  |x Logic  |x Logical topics  |x Formal logic  |x Mathematical logic  |x Mathematical set theory  |x Mathematical relations  |x Cardinality  |x Classification 
655 4 |a research-article 
773 0 8 |i Enthalten in  |t Lecture Notes-Monograph Series  |d Institute of Mathematical Statistics, 1982  |g 31(1997) vom: Jan., Seite 473-486  |w (DE-627)583817815  |w (DE-600)2460925-0  |x 07492170  |7 nnns 
773 1 8 |g volume:31  |g year:1997  |g month:01  |g pages:473-486 
856 4 0 |u https://www.jstor.org/stable/4355999  |3 Volltext 
912 |a GBV_USEFLAG_A 
912 |a SYSFLAG_A 
912 |a GBV_JST 
912 |a GBV_ILN_11 
912 |a GBV_ILN_20 
912 |a GBV_ILN_22 
912 |a GBV_ILN_23 
912 |a GBV_ILN_24 
912 |a GBV_ILN_31 
912 |a GBV_ILN_39 
912 |a GBV_ILN_40 
912 |a GBV_ILN_60 
912 |a GBV_ILN_62 
912 |a GBV_ILN_63 
912 |a GBV_ILN_65 
912 |a GBV_ILN_69 
912 |a GBV_ILN_70 
912 |a GBV_ILN_73 
912 |a GBV_ILN_90 
912 |a GBV_ILN_95 
912 |a GBV_ILN_100 
912 |a GBV_ILN_105 
912 |a GBV_ILN_110 
912 |a GBV_ILN_120 
912 |a GBV_ILN_151 
912 |a GBV_ILN_161 
912 |a GBV_ILN_170 
912 |a GBV_ILN_213 
912 |a GBV_ILN_230 
912 |a GBV_ILN_285 
912 |a GBV_ILN_293 
912 |a GBV_ILN_370 
912 |a GBV_ILN_374 
912 |a GBV_ILN_602 
912 |a GBV_ILN_702 
912 |a GBV_ILN_2001 
912 |a GBV_ILN_2003 
912 |a GBV_ILN_2005 
912 |a GBV_ILN_2006 
912 |a GBV_ILN_2007 
912 |a GBV_ILN_2008 
912 |a GBV_ILN_2009 
912 |a GBV_ILN_2010 
912 |a GBV_ILN_2011 
912 |a GBV_ILN_2014 
912 |a GBV_ILN_2015 
912 |a GBV_ILN_2018 
912 |a GBV_ILN_2020 
912 |a GBV_ILN_2021 
912 |a GBV_ILN_2026 
912 |a GBV_ILN_2027 
912 |a GBV_ILN_2044 
912 |a GBV_ILN_2050 
912 |a GBV_ILN_2056 
912 |a GBV_ILN_2057 
912 |a GBV_ILN_2061 
912 |a GBV_ILN_2088 
912 |a GBV_ILN_2107 
912 |a GBV_ILN_2110 
912 |a GBV_ILN_2190 
912 |a GBV_ILN_2938 
912 |a GBV_ILN_2947 
912 |a GBV_ILN_2949 
912 |a GBV_ILN_2950 
912 |a GBV_ILN_4012 
912 |a GBV_ILN_4035 
912 |a GBV_ILN_4037 
912 |a GBV_ILN_4046 
912 |a GBV_ILN_4112 
912 |a GBV_ILN_4125 
912 |a GBV_ILN_4126 
912 |a GBV_ILN_4242 
912 |a GBV_ILN_4249 
912 |a GBV_ILN_4251 
912 |a GBV_ILN_4305 
912 |a GBV_ILN_4306 
912 |a GBV_ILN_4307 
912 |a GBV_ILN_4313 
912 |a GBV_ILN_4322 
912 |a GBV_ILN_4323 
912 |a GBV_ILN_4324 
912 |a GBV_ILN_4325 
912 |a GBV_ILN_4326 
912 |a GBV_ILN_4335 
912 |a GBV_ILN_4338 
912 |a GBV_ILN_4346 
912 |a GBV_ILN_4367 
912 |a GBV_ILN_4392 
912 |a GBV_ILN_4393 
912 |a GBV_ILN_4700 
951 |a AR 
952 |d 31  |j 1997  |c 01  |h 473-486