Line 1: Line 1:
 +
<center><font size="4"></font>
 +
<font size="4">Questions and Comments for: '''[[KnnDensityEstimation|K-Nearest Neighbors Density Estimation]]''' </font>
 +
 +
A [https://www.projectrhea.org/learning/slectures.php slecture] by Dan Barrett
 +
</center>
 +
----
 +
 +
Please leave me comment below if you have any questions, if you notice any errors or if you would like to discuss a topic further.
 +
 +
----
 +
 +
= Questions and Comments  =
 +
 
This slecture is reviewed by Chuohao Tang
 
This slecture is reviewed by Chuohao Tang
  

Revision as of 17:51, 10 May 2014

Questions and Comments for: K-Nearest Neighbors Density Estimation

A slecture by Dan Barrett


Please leave me comment below if you have any questions, if you notice any errors or if you would like to discuss a topic further.


Questions and Comments

This slecture is reviewed by Chuohao Tang


The slecture introduces density estimation and classification technique using K nearest neighbors method.

The slecture is well organized. The problem statement and solutions described are very clear. Using one example through out the slecture is fairly illustrative. Instead of just giving the formulas, the author gives some intuition thoughts and things needs to be paid attentions to behind these formulas to help readers better understand their meanings.

There are somethings need to be improved.

  • The Bayes theorem equation is incorrectly typed. The righthand side should be divided by $ p(x) $.
  • In the equation where $ V_k(x_0) $ is defined, the part $ \sum_{l=0}^{N} \phi(\frac{x_l-x_0}{h}) = k $ I think it should not include $ x_0 $ itself. In other words, $ l $ should start from $ l=1. $
  • The visualization of density estimation is not clear. The figure title doesn’t match the describing text. Only mentioned red and blue, not other colors.

Alumni Liaison

Abstract algebra continues the conceptual developments of linear algebra, on an even grander scale.

Dr. Paul Garrett