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portada High Dimensional Data Visualization Using Self Organizing Maps
Type
Physical Book
Publisher
Author
Language
English
Pages
52
Format
Paperback
ISBN13
9783659818172

High Dimensional Data Visualization Using Self Organizing Maps

Dr. R.s. Chaudhary Dr. Vikas / Bhatia (Author) · LAP LAMBERT Academic Publishing · Paperback

High Dimensional Data Visualization Using Self Organizing Maps - Dr. R.S. Chaudhary Dr. Vikas / Bhatia

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R 726
R 726

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Synopsis "High Dimensional Data Visualization Using Self Organizing Maps "

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.

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