Probabilistic self-organizing maps for qualitative data

被引：14

作者：

Lopez-Rubio, Ezequiel ^{[1
]}

机构：

[1] Univ Malaga, Dept Comp Languages & Comp Sci, E-29071 Malaga, Spain

来源：

NEURAL NETWORKS | 2010年 / 23卷 / 10期

关键词：

Self organizing maps; Categorical data; Qualitative data; Discrete probability distribution; Unsupervised learning; Stochastic approximation; NETWORK INTRUSION DETECTION; MULTIVARIATE-BERNOULLI; CATEGORICAL-DATA; NEURAL-NETWORKS; MISSING VALUES; LATENT CLASS; MODELS; DISTRIBUTIONS; IMPUTATION; MIXTURE;

D O I：

10.1016/j.neunet.2010.07.002

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We present a self-organizing map model to study qualitative data (also called categorical data) It is based on a probabilistic framework which does not assume any prespecified distribution of the input data Stochastic approximation theory is used to develop a learning rule that builds an approximation of a discrete distribution on each unit This way the internal structure of the input dataset and the correlations between components are revealed without the need of a distance measure among the input values Experimental results show the capabilities of the model in visualization and unsupervised learning tasks (C) 2010 Elsevier Ltd All rights reserved

引用

页码：1208 / 1225

页数：18

共 50 条

[1] Probabilistic Self-Organizing Maps for Continuous Data
Lopez-Rubio, Ezequiel
[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS, 2010, 21 (10): : 1543 - 1554
[2] Probabilistic PCA Self-Organizing Maps
Lopez-Rubio, Ezequiel
Ortiz-de-Lazcano-Lobato, Juan Miguel
Lopez-Rodriguez, Domingo
[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS, 2009, 20 (09): : 1474 - 1489
[3] Probabilistic Self-Organizing Maps for Multivariate Sequences
Jaziri, Rakia
Lebbah, Mustapha
Rogovschi, Nicoleta
Bennani, Younes
[J]. 2011 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2011, : 851 - 858
[4] Self-Organizing Maps for imprecise data
D'Urso, Pierpaolo
De Giovanni, Livia
Massari, Riccardo
[J]. FUZZY SETS AND SYSTEMS, 2014, 237 : 63 - 89
[5] Data management by self-organizing maps
Kohonen, Teuvo
[J]. COMPUTATIONAL INTELLIGENCE: RESEARCH FRONTIERS, 2008, 5050 : 309 - 332
[6] A conditional, a fuzzy and a probabilistic interpretation of self-organizing maps
Giordano, Laura
Gliozzi, Valentina
Theseider Dupre, Daniele
[J]. JOURNAL OF LOGIC AND COMPUTATION, 2022, 32 (02) : 178 - 205
[7] Qualitative analysis of goat and sheep production data using self-organizing maps
Magdalena, R.
Fernandez, C.
Martin, J. D.
Soria, E.
Martinez, M.
Navarro, M. J.
Mata, C.
[J]. EXPERT SYSTEMS, 2009, 26 (02) : 191 - 201
[8] Exploring forensic data with self-organizing maps
Fei, B
Eloff, J
Venter, H
Olivier, M
[J]. ADVANCES IN DIGITAL FORENSICS, 2006, 194 : 113 - +
[9] Mining informetric data with self-organizing maps
Sotolongo-Aguilar, G
Guzmán-Sánchez, MV
Saavedra-Fernández, O
Carrillo-Calvet, HA
[J]. 8TH INTERNATIONAL CONFERENCE ON SCIENTOMETRICS AND INFORMETRICS, VOLS 1 AND 2 - ISSI-2001, PROCEEDINGS, 2001, : 665 - 673
[10] An extension of self-organizing maps to categorical data
Chen, N
Marques, NC
[J]. PROGRESS IN ARTIFICIAL INTELLIGENCE, PROCEEDINGS, 2005, 3808 : 304 - 313

← 1 2 3 4 5 →