AMSOM: Adaptive Moving Self-organizing Map for Clustering and Visualization

Gerasimos Spanakis, Gerhard Weiss

2016

Abstract

Self-Organizing Map (SOM) is a neural network model which is used to obtain a topology-preserving mapping from the (usually high dimensional) input/feature space to an output/map space of fewer dimensions (usually two or three in order to facilitate visualization). Neurons in the output space are connected with each other but this structure remains fixed throughout training and learning is achieved through the updating of neuron reference vectors in feature space. Despite the fact that growing variants of SOM overcome the fixed structure limitation they increase computational cost and also do not allow the removal of a neuron after its introduction. In this paper, a variant of SOM is proposed called AMSOM (Adaptive Moving Self-Organizing Map) that on the one hand creates a more flexible structure where neuron positions are dynamically altered during training and on the other hand tackles the drawback of having a predefined grid by allowing neuron addition and/or removal during training. Experiments using multiple literature datasets show that the proposed method improves training performance of SOM, leads to a better visualization of the input dataset and provides a framework for determining the optimal number and structure of neurons.

Paper Citation

in Harvard Style

Spanakis G. and Weiss G. (2016). AMSOM: Adaptive Moving Self-organizing Map for Clustering and Visualization . In Proceedings of the 8th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-172-4, pages 129-140. DOI: 10.5220/0005704801290140

in Bibtex Style

@conference{icaart16,
author={Gerasimos Spanakis and Gerhard Weiss},
title={AMSOM: Adaptive Moving Self-organizing Map for Clustering and Visualization},
booktitle={Proceedings of the 8th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2016},
pages={129-140},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005704801290140},
isbn={978-989-758-172-4},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 8th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - AMSOM: Adaptive Moving Self-organizing Map for Clustering and Visualization
SN - 978-989-758-172-4
AU - Spanakis G.
AU - Weiss G.
PY - 2016
SP - 129
EP - 140
DO - 10.5220/0005704801290140