Understanding High-Dimensional Spaces
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...
Κύριος συγγραφέας: | |
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Συγγραφή απο Οργανισμό/Αρχή: | |
Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
Γλώσσα: | English |
Έκδοση: |
Berlin, Heidelberg :
Springer Berlin Heidelberg : Imprint: Springer,
2012.
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Σειρά: | SpringerBriefs in Computer Science,
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Θέματα: | |
Διαθέσιμο Online: | Full Text via HEAL-Link |
Πίνακας περιεχομένων:
- Introduction
- Basic Structure of High-Dimensional Spaces
- Algorithms
- Spaces with a Single Center
- Spaces with Multiple Clusters
- Representation by Graphs
- Using Models of High-Dimensional Spaces
- Including Contextual Information
- Conclusions
- Index
- References.