Selecting the Variables that Train a Self-Organizing Map (SOM) which Best Separates Predefined Clusters

Sampsa Laine

Selecting the Variables that Train a Self-Organizing Map (SOM) which Best Separates Predefined Clusters

Sampsa Laine

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

2 Citations (Scopus)

Original language	English
Title of host publication	9th International Conference on Neural Information Processing (ICONIP'02), Singapore, November 18-22, 2002
Publication status	Published - 2002
MoE publication type	A4 Article in a conference publication

Keywords

feature extraction
self-organizing map
variable selection
visualization

Cite this

@inproceedings{e76092ec2a9346679bc10a4fb7421b3f,

title = "Selecting the Variables that Train a Self-Organizing Map (SOM) which Best Separates Predefined Clusters",

keywords = "feature extraction, self-organizing map, variable selection, visualization, feature extraction, self-organizing map, variable selection, visualization, feature extraction, self-organizing map, variable selection, visualization",

author = "Sampsa Laine",

year = "2002",

language = "English",

booktitle = "9th International Conference on Neural Information Processing (ICONIP'02), Singapore, November 18-22, 2002",

}

TY - GEN

T1 - Selecting the Variables that Train a Self-Organizing Map (SOM) which Best Separates Predefined Clusters

AU - Laine, Sampsa

PY - 2002

Y1 - 2002

KW - feature extraction

KW - self-organizing map

KW - variable selection

KW - visualization

KW - feature extraction

KW - self-organizing map

KW - variable selection

KW - visualization

KW - feature extraction

KW - self-organizing map

KW - variable selection

KW - visualization

M3 - Conference contribution

BT - 9th International Conference on Neural Information Processing (ICONIP'02), Singapore, November 18-22, 2002

ER -