Understanding high-dimensional spaces [electronic resource] / David B. Skillicorn.
High-dimensional spaces arise as a way of modelling datasets with many attributes. Such a dataset can be directly represented in a space spanned by its attributes, with each record represented as a point in the space with its position depending on its attribute values. Such spaces are not easy to wo...
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Full Text (via Springer) |
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| Format: | Electronic eBook |
| Language: | English |
| Published: |
Berlin ; New York :
Springer,
©2012.
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| Series: | SpringerBriefs in computer science.
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Table of Contents:
- Introduction
- Basic Structure of High-Dimensional Spaces
- Algorithms
- Spaces with a Single Center
- Spaces with Multiple Centers
- Representation by Graphs
- Using Models of High-Dimensional Spaces
- Including Contextual Information
- Conclusions.