@InProceedings{schneider:DagSemProc.07131.7, author = {Schneider, Petra}, title = {{Relevance Matrices in LVQ}}, booktitle = {Similarity-based Clustering and its Application to Medicine and Biology}, pages = {1--6}, series = {Dagstuhl Seminar Proceedings (DagSemProc)}, ISSN = {1862-4405}, year = {2007}, volume = {7131}, editor = {Michael Biehl and Barbara Hammer and Michel Verleysen and Thomas Villmann}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.07131.7}, URN = {urn:nbn:de:0030-drops-11332}, doi = {10.4230/DagSemProc.07131.7}, annote = {Keywords: Learning Vector Quantization, Relevance Learning, adaptive distance measure} }
The metadata provided by Dagstuhl Publishing on its webpages, as well as their export formats (such as XML or BibTeX) available at our website, is released under the CC0 1.0 Public Domain Dedication license. That is, you are free to copy, distribute, use, modify, transform, build upon, and produce derived works from our data, even for commercial purposes, all without asking permission. Of course, we are always happy if you provide a link to us as the source of the data.
Read the full CC0 1.0 legal code for the exact terms that apply: https://creativecommons.org/publicdomain/zero/1.0/legalcode
Feedback for Dagstuhl Publishing