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Infoadmin: Created page with 'This page contains general information for the class: ''CPSC445/CPSC545/MBB334/MBB545/CBB545'' '''Introduction to Data Mining''' == Course websites == * Main website ** http:…'
2010-06-03T23:12:09Z
<p>Created page with 'This page contains general information for the class: ''CPSC445/CPSC545/MBB334/MBB545/CBB545'' '''Introduction to Data Mining''' == Course websites == * Main website ** http:…'</p>
<p><b>New page</b></p><div>This page contains general information for the class:<br />
<br />
''CPSC445/CPSC545/MBB334/MBB545/CBB545''<br />
<br />
'''Introduction to Data Mining'''<br />
<br />
== Course websites ==<br />
<br />
* Main website<br />
** http://www.gersteinlab.org/courses/545/<br />
* Course wiki<br />
** http://wiki.gersteinlab.org/pubinfo/index.php/Cs545-07<br />
* Yale classes server<br />
** http://classes.yale.edu/<br />
<br />
* 2008 Wiki <br />
** http://lab.zoo.cs.yale.edu/cs445-wiki/index.php/Main_Page<br />
** [[local-copy-cs445 | local cached copy]] <br />
<br />
== Homework ==<br />
<br />
* HW2: Decision trees.<br />
** http://www.gersteinlab.org/courses/545/07-spr/hw/hw2.pdf<br />
** Due Feb 20th, 2007.<br />
<br />
* HW3: Multilinear regression.<br />
** http://www.gersteinlab.org/courses/545/07-spr/hw/hw3.pdf<br />
** http://www.gersteinlab.org/courses/545/07-spr/hw/hw3_lr.r<br />
** Due Feb 27th, 2007.<br />
<br />
* HW4: SVM.<br />
** http://www.gersteinlab.org/courses/545/07-spr/hw/hw4.pdf<br />
** http://www.gersteinlab.org/courses/545/07-spr/hw/bc_data.txt<br />
** Due Mar 11th, 2007.<br />
<br />
== Final Project ==<br />
<br />
* Suggested Term Projects. Due May 7th, 2007. Project description due by March 27, 2007<br />
** http://www.gersteinlab.org/courses/545/07-spr/project.html<br />
** http://www.gersteinlab.org/courses/545/07-spr/proj/Term_Projects_2007_final.pdf<br />
<br />
* List of proposed projects<br />
** http://spreadsheets.google.com/pub?key=pXgR9Xs-YQoFfc5bTmbwZLQ<br />
<br />
== Slides ==<br />
<br />
=== Week 1 ===<br />
* Introduction to Bioinformatics<br />
** http://www.gersteinlab.org/courses/545/07-spr/slides/cbb545b-spr07-bioinfo1-intro.ppt<br />
<br />
=== Week 3 ===<br />
* Decision tree<br />
** http://www.gersteinlab.org/courses/545/07-spr/slides/DM_DecisionTree.ppt<br />
* Ensemble methods<br />
** http://www.gersteinlab.org/courses/545/07-spr/slides/DM_Ensemble.ppt<br />
<br />
=== Week 4 ===<br />
* Multilinear and logistic regression<br />
** http://www.gersteinlab.org/courses/545/07-spr/slides/DM_multiple_regression.ppt<br />
<br />
=== Week 5 ===<br />
* SVM<br />
** http://www.gersteinlab.org/courses/545/07-spr/slides/DM_SVM.ppt<br />
** http://www.gersteinlab.org/courses/545/07-spr/slides/DM_SVM-law.ppt<br />
* Perceptron Models<br />
** http://www.gersteinlab.org/courses/545/07-spr/slides/DM_perceptron.ppt<br />
* Links <br />
** http://ranger.uta.edu/~cook/ai1/lectures/l9/l9.html<br />
<br />
=== Week 6 ===<br />
* Molecular Networks as Application of Mining<br />
** http://www.gersteinlab.org/courses/545/07-spr/slides/cbb545b-spr07-bioinfo1-intro.ppt<br />
** http://www.gersteinlab.org/courses/545/07-spr/slides/cbb545b-spr07-bioinfo2-nets.ppt<br />
<br />
* Unsupervised Learning and Clustering<br />
** http://www.gersteinlab.org/courses/545/07-spr/slides/DM_clustering.ppt<br />
** http://www.gersteinlab.org/courses/545/07-spr/slides/DM_KNN.ppt<br />
** http://www.gersteinlab.org/courses/545/07-spr/slides/DM_cluster-tan.ppt<br />
* Nice interactive k-means demo<br />
** http://www.elet.polimi.it/upload/matteucc/Clustering/tutorial_html/AppletKM.html<br />
<br />
=== Week 7 ===<br />
* Predicting Networks Through Bayesian Inference<br />
** http://www.gersteinlab.org/courses/545/07-spr/slides/cbb545b-spr07-bioinfo3-bayes1.ppt<br />
** http://www.gersteinlab.org/courses/545/07-spr/slides/cbb545b-spr07-bioinfo4-bayes2.ppt<br />
<br />
=== Week 8 ===<br />
* Applications of Spectral methods (PCA/SVD)<br />
** http://www.gersteinlab.org/courses/545/07-spr/slides/cbb545b-spr07-bioinfo5-svd1.ppt<br />
** http://www.gersteinlab.org/courses/545/07-spr/slides/cbb545b-spr07-bioinfo6-svd2.ppt<br />
<br />
=== Week 9, 10 ===<br />
Spring break<br />
<br />
=== Week 11 ===<br />
* Determining Method of Action in Drug Discovery Using Affymetrix Microarray Data<br />
** Dr. Max Kuhn, Pfizer Research Lab<br />
** http://www.gersteinlab.org/courses/545/07-spr/slides/StaphYale.pdf<br />
** http://www.gersteinlab.org/courses/545/07-spr/slides/caretYale.pdf<br />
<br />
* An Introduction to Text Mining with an Application to the Life Sciences.<br />
** Professor Michael Krauthammer, Yale Medical School<br />
** http://www.gersteinlab.org/courses/545/07-spr/slides/text_mining.mk.ppt<br />
<br />
=== Week 12 ===<br />
<br />
* A(n) (extremely) brief/crude introduction to minimum description length (MDL) principle<br />
** Jiang Du<br />
** http://www.gersteinlab.org/courses/545/07-spr/slides/mdl.jdu.ppt<br />
<br />
* Kernel PCA<br />
** Edo Liberty<br />
<br />
== Readings ==<br />
<br />
=== Week 1 ===<br />
<br />
'''Intro. to Data Mining, Overview of Data Mining in Bioinformatics'''<br />
<br />
* About Data Mining<br />
** http://www.twocrows.com/about-dm.htm<br />
* Data Mining Applications<br />
** http://www.twocrows.com/applics.htm<br />
* Data Mining In Depth: Description is Not Prediction<br />
** http://www.dmreview.com/article_sub.cfm?articleId=6388<br />
<br />
=== Week 2 ===<br />
<br />
'''Datamining workflow, Data Preprocessing and cleaning, Intro. to R and Rattle'''<br />
<br />
* Datamining workflow and presprocessing<br />
** http://www.gersteinlab.org/courses/545/07-spr/reading/aimag-kdd-overview-1996-Fayyad.pdf<br />
* Rattle<br />
** http://datamining.togaware.com/survivor/Data_Mining1.html<br />
* R<br />
** Primary web page for R.<br />
*** http://www.r-project.org<br />
** Guide<br />
*** http://cran.r-project.org/doc/contrib/Owen-TheRGuide.pdf<br />
<br />
=== Week 3 ===<br />
'''Intro. to Classification, Decision Trees'''<br />
<br />
* Classification: Basic Concepts, Decision Trees and Model Evaluation<br />
** http://www.gersteinlab.org/courses/545/07-spr/reading/tan-2005-chpt04.pdf<br />
<br />
=== Week 4 ===<br />
'''Multilinear and Logistic Regression, Support Vector Machines (SVM)'''<br />
<br />
The following chapters are available online courtesy of the authors/publishers for your personal use in this course. You may print a personal copy but you are prohibited from redistribution.<br />
<br />
* Chapter 6 of Jiawei Han and Micheline Kamber (2005). Data Mining Concepts and Techniques. Morgan Kaufmann. 2nd Ed.<br />
** http://www.gersteinlab.org/courses/545/07-spr/reading/han-2005-chpt06.pdf<br />
* Chapter 5 of Pang-Ning Tan, Michael Steinbach, and Vipin Kumar (2005). Introduction to Data Mining. Addison Wesley.<br />
** http://www.gersteinlab.org/courses/545/07-spr/reading/tan-2005-chpt05.pdf<br />
<br />
rpart<br />
<br />
* rpart R package vignette<br />
** http://cran.r-project.org/src/contrib/Descriptions/rpart.html<br />
* An Introduction to Recursive Partitioning Using the RPART Routines. Terry M. Therneau and Elizabeth J. Atkinson.<br />
** http://mayoresearch.mayo.edu/mayo/research/biostat/upload/rpartmini.pdf<br />
<br />
Logistic regression<br />
* MIT Sloan Lecture on Logistic Regression<br />
** http://ocw.mit.edu/NR/rdonlyres/Sloan-School-of-Management/15-062Data-MiningSpring2003/B2EC3803-F8A7-46CF-8B9E-D0D080E52A6B/0/logreg.pdf<br />
<br />
=== Week 6 ===<br />
<br />
* Modern trends in data mining<br />
** http://www.gersteinlab.org/courses/545/07-spr/reading/hastie_moderndatamining.pdf<br />
<br />
== Slides for courses based on reference text books ==<br />
<br />
* Ian Witten and Eibe Frank<br />
** http://books.elsevier.com/us//mk/us/subindex.asp?maintarget=companions/defaultindividual.asp</div>
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