High Dimensional Data Visualization Using Self Organizing Maps

Language: English

Published by LAP LAMBERT Academic Publishing Mai 2018, 2018

3659818178 / 9783659818172

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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.

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This item is printed on demand - it takes 3-4 days longer - Neuware -A Self-organizing map is a non-linear, unsupervised neural network that is used for data clustering and visualization of high-dimensional data. A Self-organizing map uses U-matrix to visualize the high-dimensional data and the distances between neurons on the map. However, the structure of clusters and their shapes are often distorted. For better visualization of high-dimensional data, a new approach high dimensional data visualization Self-organizing map (HVSOM) is explained. The HVSOM preserve the inter-neuron distance and better visualizes the differences between the clusters. In HVSOM, the distances between input data points on the map resemble same those in the original space. 52 pp. Englisch.

Seller Inventory # 9783659818172

Title
High Dimensional Data Visualization Using Self Organizing Maps
Author
Vikas Chaudhary
Publisher
LAP LAMBERT Academic Publishing Mai 2018
Publication year
2018
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
3659818178
ISBN 13
9783659818172
Item weight
96 grams
Dimensions
220x150x4 mm

BuchWeltWeit Ludwig Meier e.K.

Bergisch Gladbach, Germany

5-star seller

AbeBooks seller since January 11, 2012

Shipping rates from Germany to U.S.A.

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BuchWeltWeit Ludwig Meier e.K.

Germany