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[[Category:ECE662]]
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[[Category:decision theory]]
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[[Category:lecture notes]]
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[[Category:pattern recognition]]
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[[Category:slecture]]
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=The Curse of Dimensionality=
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from [[Lecture_2_-_Decision_Hypersurfaces_OldKiwi|Lecture 2, ECE662, Spring 2010]]
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Refers to the problem caused by exponential growth of hypervolume as a function of dimensionality. This term was coined by Richard Bellman in 1961.
 
Refers to the problem caused by exponential growth of hypervolume as a function of dimensionality. This term was coined by Richard Bellman in 1961.
  
 
As stated in [[Lecture 3 - Bayes classification_Old Kiwi]],
 
As stated in [[Lecture 3 - Bayes classification_Old Kiwi]],
 
The curse of dimensionality starts at d>17-23. There are no clusters or groupings of data points when d>17. In practice each point turns to be a cluster on its own and as a result this explodes into a high dimensional feature vectors which are impossible to handle in computation.
 
The curse of dimensionality starts at d>17-23. There are no clusters or groupings of data points when d>17. In practice each point turns to be a cluster on its own and as a result this explodes into a high dimensional feature vectors which are impossible to handle in computation.
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[[Lecture_2_-_Decision_Hypersurfaces_OldKiwi|Back to Lecture 2, ECE662, Spring 2010]]

Latest revision as of 09:57, 10 June 2013


The Curse of Dimensionality

from Lecture 2, ECE662, Spring 2010


Refers to the problem caused by exponential growth of hypervolume as a function of dimensionality. This term was coined by Richard Bellman in 1961.

As stated in Lecture 3 - Bayes classification_Old Kiwi, The curse of dimensionality starts at d>17-23. There are no clusters or groupings of data points when d>17. In practice each point turns to be a cluster on its own and as a result this explodes into a high dimensional feature vectors which are impossible to handle in computation.


Back to Lecture 2, ECE662, Spring 2010

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