High Dimensional Data Visualization Using Self Organizing Maps
- Editore:
LAP Lambert Academic Publishing
- EAN:
9783659818172
- ISBN:
3659818178
- Pagine:
- 52
- Formato:
- Paperback
- Lingua:
- Tedesco
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Descrizione 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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€ 30.87
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