(copy from lect. 3)
 
(One intermediate revision by the same user not shown)
Line 1: Line 1:
 +
[[Category:ECE662]]
 +
[[Category:decision theory]]
 +
[[Category:lecture notes]]
 +
[[Category:pattern recognition]]
 +
[[Category:slecture]]
 +
 +
=The Curse of Dimensionality=
 +
from [[Lecture_2_-_Decision_Hypersurfaces_OldKiwi|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.
 
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_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

Alumni Liaison

Prof. Math. Ohio State and Associate Dean
Outstanding Alumnus Purdue Math 2008

Jeff McNeal