Relational Neural Gas

Paaßen B (2018) : Bielefeld University. doi:10.4119/unibi/2916980.

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Abstract / Bemerkung
This is a Java 7, fully MATLAB (R) compatible implementation of _Relational neural gas_. Relational neural gas is a clustering algorithm for distance data, meaning that you put in a matrix of pairwise distances D as well as a number of clusters K and you receive a distribution of your data points into K distinct clusters. It has first been proposed by [Hammer and Hasenfuss (2007)](https://doi.org/10.1007/978-3-540-74565-5_16) and is an extension of the _neural gas_ algorithm by [Martinetz and Schulten (1991)](https://www.ks.uiuc.edu/Publications/Papers/PDF/MART91B/MART91B.pdf). The basic idea of neural gas is to represent each cluster k in terms of a prototype wk which is responsible for all data points for which this prototype is the closest prototype. This prototype-based representation has two main advantages compared to other clustering methods: 1. It permits to extend the clustering to new data points by assigning new data points to their closest prototype (out-of-sample extension). 2. It permits to inspect the data set in terms of representative data points (i.e. the prototypes).
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This Relational Neural Gas is made available under the Open Database License: http://opendatacommons.org/licenses/odbl/1.0. Any rights in individual contents of the database are licensed under the Database Contents License: http://opendatacommons.org/licenses/dbcl/1.0/
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Paaßen B. (2018): Relational Neural Gas. Bielefeld University. doi:10.4119/unibi/2916980.
Paaßen, B. (2018). Relational Neural Gas. Bielefeld University. doi:10.4119/unibi/2916980
Paaßen, B. (2018). Relational Neural Gas. Bielefeld University. doi:10.4119/unibi/2916980.
Paaßen, B., 2018. Relational Neural Gas. Bielefeld University. doi:10.4119/unibi/2916980
B. Paaßen, Relational Neural Gas. Bielefeld University, 2018. doi:10.4119/unibi/2916980.
Paaßen, B.: Relational Neural Gas. Bielefeld University (2018). doi:10.4119/unibi/2916980.
Paaßen, Benjamin. Relational Neural Gas. Bielefeld University, 2018. doi:10.4119/unibi/2916980
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Externes Material:
Wissenschaftliche Version
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The original research paper by Hammer and Hasenfuss describing Relational Neural Gas.
Software:
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Publically available GitLab page including the source files for this distribution.

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