Line 6: Line 6:
  
 
<center><font size= 4>
 
<center><font size= 4>
Parzen window method for classification
+
Parzen window method and classification
 
</font size>
 
</font size>
  
Line 14: Line 14:
 
</center>
 
</center>
 
----
 
----
 +
in progess....
 
----
 
----
 +
Unlike parametric density estimation methods, non-parametric approaches locally estimate density function by a small number of neighboring samples [4] and therefore show less accurate estimation results. In spite of their accuracy, however, the performance of classifiers designed using these estimates is very satisfactory.\\
 +
 
Post your slecture material here. Guidelines:
 
Post your slecture material here. Guidelines:
 
*If you are making a text slecture
 
*If you are making a text slecture

Revision as of 07:53, 30 April 2014


Parzen window method and classification

A slecture by ECE student Chiho Choi

Partly based on the ECE662 Spring 2014 lecture material of Prof. Mireille Boutin.


in progess....


Unlike parametric density estimation methods, non-parametric approaches locally estimate density function by a small number of neighboring samples [4] and therefore show less accurate estimation results. In spite of their accuracy, however, the performance of classifiers designed using these estimates is very satisfactory.\\

Post your slecture material here. Guidelines:

  • If you are making a text slecture
    • Type text using wikitext markup languages
    • Type all equations using latex code between <math> </math> tags.
    • You may include links to other Project Rhea pages.

$ \rightarrow $




Questions and comments

If you have any questions, comments, etc. please post them on this page.


Back to ECE662, Spring 2014

Alumni Liaison

BSEE 2004, current Ph.D. student researching signal and image processing.

Landis Huffman