A Novel Metric Embedding Optimal Normalization Mechanism for Clustering of Series Data
Summary :
Clustering is indispensable to obtain a general view of series data from a number of data such as gene expression profiles. We propose a novel metric for clustering. The proposed metric automatically normalizes data to minimize a logarithmic scale distance between the data series.
- Publication
- IEICE TRANSACTIONS on Information Vol.E91-D No.9 pp.2369-2371
- Publication Date
- 2008/09/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1093/ietisy/e91-d.9.2369
- Type of Manuscript
- LETTER
- Category
- Biological Engineering
Authors
Keyword
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Shigeyuki MITSUI, Katsumi SAKATA, Hiroya NOBORI, Setsuko KOMATSU, "A Novel Metric Embedding Optimal Normalization Mechanism for Clustering of Series Data" in IEICE TRANSACTIONS on Information,
vol. E91-D, no. 9, pp. 2369-2371, September 2008, doi: 10.1093/ietisy/e91-d.9.2369.
Abstract: Clustering is indispensable to obtain a general view of series data from a number of data such as gene expression profiles. We propose a novel metric for clustering. The proposed metric automatically normalizes data to minimize a logarithmic scale distance between the data series.
URL: https://global.ieice.org/en_transactions/information/10.1093/ietisy/e91-d.9.2369/_p
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@ARTICLE{e91-d_9_2369,
author={Shigeyuki MITSUI, Katsumi SAKATA, Hiroya NOBORI, Setsuko KOMATSU, },
journal={IEICE TRANSACTIONS on Information},
title={A Novel Metric Embedding Optimal Normalization Mechanism for Clustering of Series Data},
year={2008},
volume={E91-D},
number={9},
pages={2369-2371},
abstract={Clustering is indispensable to obtain a general view of series data from a number of data such as gene expression profiles. We propose a novel metric for clustering. The proposed metric automatically normalizes data to minimize a logarithmic scale distance between the data series.},
keywords={},
doi={10.1093/ietisy/e91-d.9.2369},
ISSN={1745-1361},
month={September},}
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TY - JOUR
TI - A Novel Metric Embedding Optimal Normalization Mechanism for Clustering of Series Data
T2 - IEICE TRANSACTIONS on Information
SP - 2369
EP - 2371
AU - Shigeyuki MITSUI
AU - Katsumi SAKATA
AU - Hiroya NOBORI
AU - Setsuko KOMATSU
PY - 2008
DO - 10.1093/ietisy/e91-d.9.2369
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E91-D
IS - 9
JA - IEICE TRANSACTIONS on Information
Y1 - September 2008
AB - Clustering is indispensable to obtain a general view of series data from a number of data such as gene expression profiles. We propose a novel metric for clustering. The proposed metric automatically normalizes data to minimize a logarithmic scale distance between the data series.
ER -
English
