(The ChangeLog)
(The ChangeLog)
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[[User:tha|Thanh Huy Ha]]
 
[[User:tha|Thanh Huy Ha]]
 
* 2008/04/07 -- Created the page [[Editing technique_OldKiwi]], a very useful technique which helps us to reduce memory and computation expenses in K-nearest neighbor method.
 
* 2008/04/07 -- Created the page [[Editing technique_OldKiwi]], a very useful technique which helps us to reduce memory and computation expenses in K-nearest neighbor method.
 +
* 2008/04/17 -- Created the page [[Leave-one-out Cross Validation_OldKiwi]], a technique which helps us to choose the model for KNN or ANN claissification method.
  
 
[[User:tchen|Thomas Chen]]
 
[[User:tchen|Thomas Chen]]

Revision as of 13:01, 17 April 2008

Page Formatting

Please keep your changes logged under your name in chronological order (most recent change appended to the bottom of your list). If your name is not included yet, please include it, retaining the alphabetization of the users by name. Entries are sorted by first names alphabetically.

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To aid the grader, please try to be as exact as possible' in your description. Number your figures and equations and specify those in your ChangeLog entry. Also give a hyperlink to the page(s) you edited.

Example

Bunyamin Sisman

The ChangeLog

KyoHyouk Kim

  • 2008/04/07 -- Add links for clustering techniques
  • 2008/04/07 -- Add figure of impurity function on Lecture 21

Abhishek Arora

Bunyamin Sisman

  • 2008/04/06 -- Added some explanations and a figure to lecture 22 for clustering.
  • 2008/04/06 -- Introduced different kinds of clustering algorithms and a simple example with a figure for image segmentation and compression using k-means algorithm in lecture 22.
  • 2008/04/13 -- Added some explanations, links and a animated gif for Minimum spanning tree algorithms to lecture 24.
  • 2008/04/16 -- Added some explanations to Farthest Neighbor Algorithm.

Dalton Lunga

Elvin Bernard

Fengqing Zhu

Gaurav Srivastava

Hector Santos

Jinha Jung

Jinyoung Kim

Johannes Cilliers

Josiah Yoder

Clustering, Statistical Clustering Methods, and Clustering by finding valleys of densities. Further discussion and figures would still be helpful.

Jungtag Gong

KaKi Ng

Kihwan Han


Landis Huffman

Leonardo Bachega

Madhur Gupta

  • 2008/04/01 -- Created the page for Lecture 21 - Decision Trees(Continued)_OldKiwi. Added the example of fruits, and Three crucial questions to answer.
  • 2008/04/03 -- Added to Lecture 22 - Decision Trees and Clustering_OldKiwi the section named "Clustering as a useful technique for searching in databases". This includes the example of Dewey system with figure, and the example of face recognition without figure.
  • 2008/04/08 -- Added the first set of notes to Lecture 23 - Spanning Trees_OldKiwi, namely the section "Clustering Method, given the pairwise distances", with the text, a distance table, a figure showing the ideal clustering situation, and a figure presenting the case when the algorithm won't work well.
  • 2008/04/16 -- Added the set of lecture notes for Lecture 25 - Clustering Algorithms_OldKiwi under the section "Clustering Methods - A summary". This includes a table for summary of Clustering methods titled "Figure 1". It also includes some text explaining defect in these methods and motivation for feature vector-based methods, which involve projection to lower dimensions. I do not provide the illustrating figures for the text, but I annotate for the same at two places.

Marc Bosch

Neil Bedwell

Patrick Clough

Rahul Srinivasa Raghavan

  • 2008/04/06 -- Ported over all PDF's, pertaining to 1st Exam_OldKiwi of EC301, from old kiwi to new kiwi.
  • 2008/04/06 -- Ported over contents, and added some materials pertaining to the Exam section, from old kiwi to new kiwi, for EC301.
  • 2008/04/13 -- Ported over all materials, including PDF's pertaining to ECE 301, for 2nd Exam_OldKiwi
  • 2008/04/13 -- Transferred all the contents of 3rd Exam_OldKiwi from old kiwi to the new one.

Saranya Raghavan

  • 2008/04/06 -- Added link to commercial and free software for Classification using Decision Trees (Tools_OldKiwi).
  • 2008/04/06 -- Added Publication #18 (A Scalable Decision Tree Algorithm) to Publications_OldKiwi, and provided an abstract.
  • 2008/04/16 -- Added a page on Clustering Algorithms_OldKiwi, explaining the types of clustering methods and links to software

Seong Jun Park

  • 2008/04/04 -- Moved several images about Neural Network from old kiwi website to the lecture 13.
  • 2008/04/06 -- Added lecture notes about image segmentation.
  • 2008/04/07 -- Added figures about a sample tree and entropy impurity example in Lecture 22.
  • 2008/04/10 -- Added lecture and figures of spanning tree example in Lecture 23.
  • 2008/04/10 -- Linked the several glossaries used in the graph theory.

Shuowen Hu

  • 2008/04/06 -- Added Figure 5 in Lecture 22 illustrating clustering, specifically hierarchial clustering with human pictures
  • 2008/04/06 -- Added figure labels for all pictures in Lecture 22
  • 2008/04/16 -- Created Figure 4 in Lecture 23 illustrating clustering with a graph theory approach
  • 2008/04/16 -- Added figure labels for all pictures in Lecture 23

Singanallur V Venkatakrishnan

Stephen Rudolph

Thanh Huy Ha

  • 2008/04/07 -- Created the page Editing technique_OldKiwi, a very useful technique which helps us to reduce memory and computation expenses in K-nearest neighbor method.
  • 2008/04/17 -- Created the page Leave-one-out Cross Validation_OldKiwi, a technique which helps us to choose the model for KNN or ANN claissification method.

Thomas Chen

  • 2008/04/02 -- Edited Lecture 21 - added comment on CART Methodology
  • 2008/04/02 -- Edited Lecture 21 - created image ECE662_lect21_stopping.jpg and comments about it at the bottom of the page
  • 2008/04/08 -- Edited Lecture 23 - Created animated image ECE662_lect23.gif and created example in lecture notes
  • 2008/04/10 -- Edited Lecture 24 - Added notes from agglomerate algorithms for hierarchical clustering

Tzu-Cheng Chuang

Yamini Nimmagadda

Mandoye Ndoye


Yun-ting Su

  • 2008/04/06 -- Created Figure 6 in Lecture 22 to illustrate an example of clustering with image segmentation.
  • 2008/04/06 -- Wrote lecture note about image segmentation to describe Figure 6 in Lecture 22
  • 2008/04/16 -- Created Figure 7 in Lecture 24 Minimum Spanning Tree Methods (MST) illustrating Farthesr Neighbor distance with similarity scale
  • 2008/04/16 -- Added figure labels following by orderes for all pictures in Lecture 24 Minimum Spanning Tree Methods (MST)

Alumni Liaison

Ph.D. 2007, working on developing cool imaging technologies for digital cameras, camera phones, and video surveillance cameras.

Buyue Zhang