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| + | [[Category:decision theory]] | ||
| + | [[Category:lecture notes]] | ||
| + | [[Category:pattern recognition]] | ||
| + | [[Category:slecture]] | ||
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| + | =The Curse of Dimensionality= | ||
| + | from [[Lecture_1_-_Introduction_OldKiwi|Lecture 1, 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. | 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. | ||
| + | ---- | ||
| + | [[Lecture_1_-_Introduction_OldKiwi|Back to Lecture 1, ECE662, Spring 2010]] | ||
Revision as of 09:55, 10 June 2013
The Curse of Dimensionality
from Lecture 1, 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.
