(New page: Category:ECE662Spring2014Boutin Category:ECE Category:ECE662 Category:pattern recognition Category:discussion == Discussion about Data for homework 1== [[2014_Spring_...)
(No difference)

Revision as of 07:47, 9 February 2014


Discussion about Data for homework 1

ECE662, Spring 2014


  • Question from a student email:"In the Internet I find a lot if data sets, but all of them have n-dim feature vectors. It's very hard to find a feature vector with only one variable. It there a way that we can convey the n-dim feature vector to 1-d feature? If in common, not, do you have any suggestions on where I could find good 1-d feature data?"
    • You can simply use the first dimension of the feature vector as a one-dimensional feature. You could also use the second dimension, or the third dimension, etc. -pm

Back to main ECE662 Spring 2014 course wiki

Alumni Liaison

Ph.D. on Applied Mathematics in Aug 2007. Involved on applications of image super-resolution to electron microscopy

Francisco Blanco-Silva