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LVQ can be a source of great help in classifying text documents.{{Citation needed|date=December 2019|reason=removed citation to predatory publisher content}}
== Algorithm ==
Below follows an informal description.<br>
The algorithm consists of three basic steps. The algorithm's input is:
Note: <math>\vec{w_i}</math> and <math>\vec{x}</math> are [[vector space|vectors]] in feature space.
== Variants ==
* LVQ2.1
* Generalized LVQ (GLVQ) {{cite web |url=https://papers.nips.cc/paper/1995/file/9c3b1830513cc3b8fc4b76635d32e692-Paper.pdf |title=Generalized Learning Vector Quantization |last= |first= |date= |website=nips.cc |publisher=NeurIPS Proceedings |access-date=25 August 2022 |quote=}}
* Generalized Relevance LVQ (GRLVQ) <ref name="HammerVillmann2002">{{cite journal | last1 = Hammer | first1 = Barbara | last2 = Villmann | first2 = Thomas | title = Generalized relevance learning vector quantization | journal = Neural Networks | date = October 2002 | volume = 15 | issue = 8–9 | pages = 1059–1068 | issn = 0893-6080 | doi = 10.1016/S0893-6080(02)00079-5 | pmid = | url = }}</ref>
* Generalized Matrix LVQ (GMLVQ) <ref name="SchneiderBiehlHammer2009">{{cite journal | last1 = Schneider | first1 = Petra | last2 = Biehl | first2 = Michael | last3 = Hammer | first3 = Barbara | title = Adaptive Relevance Matrices in Learning Vector Quantization | journal = Neural Computation | date = December 2009 | volume = 21 | issue = 12 | pages = 3532–3561 | issn = 0899-7667 | eissn = 1530-888X | doi = 10.1162/neco.2009.11-08-908 | pmid = 19764875 | url = }}</ref>
* Relational GLVQ (RGLVQ) <ref name="HammerSchleifZhu2011">{{cite book | title = Neural Information Processing | last1 = Hammer | first1 = Barbara | last2 = Schleif | first2 = Frank-Michael | last3 = Zhu | first3 = Xibin | chapter = Relational Extensions of Learning Vector Quantization | date = 2011 | pages = 481–489 | publisher = Springer Berlin Heidelberg | issn = 0302-9743 | eissn = 1611-3349 | doi = 10.1007/978-3-642-24958-7_56 | url = }}</ref>
* Median GLVQ (MGLVQ) <ref name="NebelHammerFrohberg2015">{{cite journal | last1 = Nebel | first1 = David | last2 = Hammer | first2 = Barbara | last3 = Frohberg | first3 = Kathleen | last4 = Villmann | first4 = Thomas | title = Median variants of learning vector quantization for learning of dissimilarity data | journal = Neurocomputing | date = December 2015 | volume = 169 | pages = 295–305 | issn = 0925-2312 | doi = 10.1016/j.neucom.2014.12.096 | pmid = | url = }}</ref>
* Limited Rank Matrix LVQ (LiRaMLVQ) <ref name="BunteSchneiderHammer2012">{{cite journal | last1 = Bunte | first1 = Kerstin | last2 = Schneider | first2 = Petra | last3 = Hammer | first3 = Barbara | last4 = Schleif | first4 = Frank-Michael | last5 = Villmann | first5 = Thomas | last6 = Biehl | first6 = Michael | title = Limited Rank Matrix Learning, discriminative dimension reduction and visualization | journal = Neural Networks | date = February 2012 | volume = 26 | pages = 159–173 | issn = 0893-6080 | doi = 10.1016/j.neunet.2011.10.001 | pmid = 22041220 | url = }}</ref>
* Robust soft LVQ (RSLVQ) <ref name="SeoObermayer2003">{{cite journal | last1 = Seo | first1 = Sambu | last2 = Obermayer | first2 = Klaus | title = Soft Learning Vector Quantization | journal = Neural Computation | date = 1 July 2003 | volume = 15 | issue = 7 | pages = 1589–1604 | issn = 0899-7667 | eissn = 1530-888X | doi = 10.1162/089976603321891819 | pmid = 12816567 | url = }}</ref>
* Border-sensitive GLVQ (BSGLVQ) <ref name="KadenRiedelHermann2014">{{cite journal | last1 = Kaden | first1 = Marika | last2 = Riedel | first2 = Martin | last3 = Hermann | first3 = Wieland | last4 = Villmann | first4 = Thomas | title = Border-sensitive learning in generalized learning vector quantization: an alternative to support vector machines | journal = Soft Computing | date = 20 November 2014 | volume = 19 | issue = 9 | pages = 2423–2434 | issn = 1432-7643 | eissn = 1433-7479 | doi = 10.1007/s00500-014-1496-1 | pmid = | url = }}</ref>
== References ==
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