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[https://www.projectrhea.org/learning/slectures.php Slectures]
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[[Category:slecture]]
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[[Category:ECE662Spring2014Boutin]]
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[[Category:ECE]]
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[[Category:ECE662]]
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[[Category:pattern recognition]]
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[[Category:statistics]]
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[[Category:probability]]
  
 
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<center><font size= 4>
'''The Boutin Lectures on Statistical Pattern Recognition'''
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'''The [http://mireilleboutin.com Boutin] Lectures on Statistical Pattern Recognition'''
 
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[https://www.projectrhea.org/learning/slectures.php Slectures] by Students in the Spring 2014 Class
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Multilingual [http://www.projectrhea.org/learning/slectures.php Slectures] by Students in the Spring 2014 Class of [[ECE662]]
 
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==0. Foreword by Professor Boutin==
 
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==1. Background Material ==
Foreword by Professor Boutin
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*Whitening and Coloring Transforms
 
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**[[ECE662 Whitening and Coloring Transforms S14 MH|Text slecture in English]], by [[User:Mhossain|Maliha Hossain]] <span style="color:GREEN">Very clear!</span>  
*Slectures on Probability and Statistics
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*How to generate random n dimensional data from two categories with different priors (use these methods to generate data for homework)
**[[ECE662 Whitening and Coloring Transforms S14 MH|Whitening and Coloring Transforms]], by [[User:Mhossain|Maliha Hossain]] <span style="color:GREEN">OK</span>  
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**[[Generating random data with controlled prior probabilities slecture ECE662S14 Gheith|Video slecture in English]] by Alex Gheith <span style="color:GREEN">Newbies can start here</span>  
**How to generate random n dimensional data from two categories with different priors  
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**[[How to generate random n dimensional data from two categories with different priors slecture Minwoong Kim ECE662 Spring 2014|Video slecture in Korean ]], by Minwoong Kim <span style="color:GREEN">Newbies can start here- if they speak Korean</span>  
***[[Generating random data with controlled prior probabilities slecture ECE662S14 Gheith|Video slecture in English]] by Alex Gheith <span style="color:GREEN">OK</span>  
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**[[How to generate random n dimensional data from two categories with different priors slecture Minwoong Cho ECE662 Spring 2014|Video slecture in Korean ]], by Hyun Dok Cho <span style="color:GREEN">Newbies can start here- if you they speak Korean</span>  
***[[How to generate random n dimensional data from two categories with different priors slecture Minwoong Kim ECE662 Spring 2014|Video slecture in Korean ]], by Minwoong Kim <span style="color:GREEN">OK</span>  
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**[[The principles for how to generate random samples from a Gaussian distribution|Text slecture in English]] by Joonsoo Kim <span style="color:GREEN">More Advanced</span>  
***[[How to generate random n dimensional data from two categories with different priors slecture Minwoong Cho ECE662 Spring 2014|Video slecture in Korean ]], by Hyun Dok Cho <span style="color:GREEN">OK</span>  
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**[[Generation of N-dimensional normally distributed random numbers from two categories with different priors|Text slecture in English]] by Jonghoon Jin <span style="color:GREEN">More Advanced</span>
***[[The principles for how to generate random samples from a Gaussian distribution|Text slecture in English]] by Joonsoo Kim <span style="color:GREEN">OK</span>
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*Principal Component Analysis (PCA)  
***[[Generation of N-dimensional normally distributed random numbers from two categories with different priors|Text slecture in English]] by Jonghoon Jin <span style="color:GREEN">OK</span>  
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**[[PCA|Text slecture in English]], by [http://web.ics.purdue.edu/~zhou338/ Tian Zhou] <span style="color:GREEN">Starts very slowly.</span>  
**Principal Component Analysis (PCA)  
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**[[PCA Theory Examples|Text slecture in English]], by Sujin Jang <span style="color:GREEN">Jumps right into linear algebra at the beginning.</span>
***[[PCA|Text slecture in English]], by [http://web.ics.purdue.edu/~zhou338/ Tian Zhou] <span style="color:GREEN">OK</span>  
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**[[Pca khalid|Video slecture in English]], by Khalid Tahboub <span style="color:GREEN">Clearly explains why it's not good when trying to recognize patterns</span>
***[[PCA Theory Examples|Text slecture in English]], by Sujin Jang <span style="color:GREEN">OK</span>  
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**[[Kernel PCA|Video slecture in English, and Chinese]], by Tsung Tai Yeh <span style="color:GREEN">More Advanced. Covers kernel PCA.</span>
***[[Kernel PCA|Video slecture in English, and Chinese]], by Tsung Tai Yeh <span style="color:GREEN">OK</span>  
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*The Curse of Dimensionality  
***[[Pca khalid|Video slecture in English]], by Khalid Tahboub <span style="color:GREEN" />  
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**[[Curse of Dimensionality|Text slecture in English]], and [[Curse of Dimensionality Chinese|in Chinese]] by Haonan Yu <span style="color:GREEN">Text flows nicely. Fun read.</span>
*Slectures on Curse of Dimensionality  
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==2. Bayes Rule ==
**[[Curse of Dimensionality|Text slecture in English]], and [[Curse of Dimensionality Chinese|in Chinese]] by Haonan Yu USE SAME COMMENT PAGE FOR BOTH ENGLISH AND CHINESE VERSION
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*Bayes Rule in Layman's Terms  
*Slectures on Bayes Rule  
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**[[Introduction to Bayes' Rule|Video slecture in Spanish]] by Francis Phillip  
**Bayes Rule in Layman's Terms  
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*Derivation of Bayes Rule  
***[[Introduction to Bayes' Rule|Video slecture in Spanish]] by Francis Phillip <span style="color:GREEN">OK</span>
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**[[Derivation of Bayes rule Anonymous7|Text slecture in English]] By Anonymous7  
**Derivation of Bayes Rule  
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**[[From Bayes Theorem to Pattern Recognition via Bayes Rule|Text slecture in English]] by [http://varunvasudevan.com/ Varun Vasudevan]  
***[[Derivation of Bayes rule Anonymous7|Text slecture in English]] By Anonymous7 <span style="color:GREEN">OK</span>
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**[[Derivation of Bayes' Rule from Bayes' Theorem|Video slecture in English]] by Nadra Guizani  
***[[From Bayes Theorem to Pattern Recognition via Bayes Rule|Text slecture in English]] by [http://varunvasudevan.com/ Varun Vasudevan] <span style="color:GREEN">OK</span>
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**[[Derivation Bayes Rule slecture ECE662 Spring2014 Kim|Video slecture in English]] by Jieun Kim  
***[[Derivation of Bayes' Rule from Bayes' Theorem|Video slecture in English]] by Nadra Guizani <span style="color:GREEN">OK</span>
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**[[Derivation of Bayes rule In Greek|Text slecture in Greek]] by Stylianos Chatzidakis
***[[Derivation Bayes Rule slecture ECE662 Spring2014 Kim|Video slecture in English]] by Jieun Kim <span style="color:GREEN">OK</span>
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**[[Derivation of Bayes rule In Chinese|Text slecture in Chinese]] by Weibao Wang  
***[[Derivation of Bayes rule In Greek|Text slecture in Greek]] by Stylianos Chatzidakis <span style="color:GREEN">OK</span>
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*Optimality of Bayes Rule  
***[[Derivation of Bayes rule In Chinese|Text slecture in Chinese]] by Weibao Wang <span style="color:GREEN">OK</span>
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**[[Slecture optimality bayes decision rule michaux ECE662S14|Video slecture in English]] by Aaron Michaux  
**Optimality of Bayes Rule  
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**[[Kjw810313|Video slecture in Korean]] by Jeong-wan Kim
***[[Slecture optimality bayes decision rule michaux ECE662S14|Video slecture in English]] by Aaron Michaux <span style="color:GREEN">OK</span>
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*Upper Bounds for Bayes Error  
***[[Kjw810313|Video slecture in Korean]] by Jeong-wan Kim <span style="color:GREEN">OK</span>
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**[[Upper Bounds for Bayes Error|Text slecture in English]] by G. M. Dilshan Godaliyadda   
**Upper Bounds for Bayes Error  
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**[[Test|Text slecture in English (includes the derivation of Chernoff Distance)]] by Jeehyun Choe
***[[Upper Bounds for Bayes Error|Text slecture in English]] by G. M. Dilshan Godaliyadda   
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*Bayes Rule to Minimize Risk  
***[[Upper Bound for Bayes error|Text slecture in English]] by Yihan Ding <span style="color:RED">MATERIAL PLAGIARIZED. NOT EVEN A CITATION IS GIVEN</span>
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**[[Slecture Bayes rule to minimize risk Andy Park ECE662 Spring 2014|Video slectures in English]], by Andy Park
***[[Test|Text slecture in English (includes the derivation of Chernoff Distance)]] by Jeehyun Choe <span style="color:GREEN">OK</span>
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**[[Ness slecture 2014|Text slecture in Chinese]] by Robert Ness  
**Bayes Rule to Minimize Risk  
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**[[Bayes Rule Minimize Risk Dennis Lee|Text slecture in English]] by Dennis Lee
***[[Slecture Bayes rule to minimize risk Andy Park ECE662 Spring 2014|Video slectures in English]], by Andy Park <span style="color:GREEN">OK</span>
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*Bayes Rule for Normally Distributed Features  
***[[Ness slecture 2014|Text slecture in Chinese]] by Robert Ness <span style="color:GREEN">OK</span>
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**[[Discussion about Discriminant Functions for the Multivariate Normal Density|Text slecture in English]] by Yanzhe Cui  
***[[Bayes Rule Minimize Risk Dennis Lee|Text slecture in English]] by Dennis Lee <span style="color:GREEN">OK</span>
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**[[Bayes Rule for 1-dimensional and N-dimensional feature spaces|Text slecture in English]] by Jihwan Lee  
**Bayes Rule for Normally Distributed Features  
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*Bayes rule in practice  
***[[Discussion about Discriminant Functions for the Multivariate Normal Density|Text slecture in English]] by Yanzhe Cui  
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**[[Bayes rule in practice|Text slecture in English]] by Lu Wang
***[[Bayes Rule for 1-dimensional and N-dimensional feature spaces|Text slecture in English]] by Jihwan Lee <span style="color:GREEN">OK</span>
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**[[662slecture tang|Text slecture in English]] by Chuohao Tang
**Bayes rule in practice  
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*Neyman-Pearson test and ROC curves  
***[[Bayes rule in practice|Text slecture in English]] by Lu Wang <span style="color:GREEN">OK</span>
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**[[Neyman-Pearson Lemma and Receiver Operating Characteristic Curve|Text slecture in English]] by [https://engineering.purdue.edu/~lee714/ Soonam Lee]  
***[[662slecture tang|Text slecture in English]] by Chuohao Tang <span style="color:GREEN">OK</span>
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**[[ROC curve analysis slecture ECE662 Spring0214 Sun|Video slecture in English]] by Jianxin Sun  
*Slectures on Neyman-Pearson test and ROC curves  
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**[[ECE662 roc|Text slecture in English]] by Hao Lin
**[[Neyman-Pearson Lemma and Receiver Operating Characteristic Curve|Text slecture in English]] by [https://engineering.purdue.edu/~lee714/ Soonam Lee] <span style="color:GREEN">OK</span>
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==3. Global (parametric) Density Estimation Methods==
**[[ROC curve analysis slecture ECE662 Spring0214 Sun|Video slecture in English]] by Jianxin Sun <span style="color:GREEN">OK</span>
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*Maximum Likelihood Estimation (MLE)  
**[[ECE662 roc|Text slecture in English]] by Hao Lin <span style="color:GREEN">OK</span>
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**[[Mle tutorial|Text slecture in English]] by Sudhir Kylasa  
*Slectures on Density Estimation  
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**[[Maximum Likelihood Estimation Analysis for various Probability Distributions|Text slecture in English]] by Hariharan Seshadri
**Maximum Likelihood Estimation (MLE)  
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**[[Video slecture in English: Introduction to Maximum Likelihood Estimation|Video slecture in English]] by Anantha Raghuraman  
***[[Mle tutorial|Text slecture in English]] by Sudhir Kylasa <span style="color:GREEN">OK</span>
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**[[Convergence of the Maximum Likelihood Estimator over Multiple Trials|Video slecture in English]] by [http://web.ics.purdue.edu/~scarver/ Spencer Carver]  
***[[Maximum Likelihood Estimation Analysis for various Probability Distributions|Text slecture in English]] by Hariharan Seshadri <span style="color:GREEN">OK</span>
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**[[Maximum Likelihood Estimators and Examples|Text slecture in English]] by Lu Zhang
***[[Video slecture in English: Introduction to Maximum Likelihood Estimation|Video slecture in English]] by Anantha Raghuraman <span style="color:GREEN">OK</span>
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**[[SlectureKeehwanECE662Spring14|Video slecture in English]] by Keehwan Park  
***[[Convergence of the Maximum Likelihood Estimator over Multiple Trials|Video slecture in English]] by [http://web.ics.purdue.edu/~scarver/ Spencer Carver] <span style="color:GREEN">OK</span>
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**[[MLEforGMM|Text slecture in English]] by Wen Yi  
***[[Maximum Likelihood Estimators and Examples|Text slecture in English]] by Lu Zhang <span style="color:GREEN">OK</span>
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**[[ECE662Selecture zhenpengMLE|Text slecture in English]] by Zhenpeng Zhao  
***[[SlectureKeehwanECE662Spring14|Video slecture in English]] by Keehwan Park <span style="color:GREEN">OK</span>
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*Bayesian Estimation (BPE)  
***[[MLEforGMM|Text slecture in English]] by Wen Yi  
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**[[Bayes Parameter Estimation|Text slecture in English]] by Haiguang Wen
***[[ECE662Selecture zhenpengMLE|Text slecture in English]] by Zhenpeng Zhao  
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**[[Bayersian Parameter Estimation: Gaussian Case|Text slecture in English]], by Shaobo Fang  
**Bayesian Estimation (BPE)  
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**[[Bayes Parameter Estimation with examples|Text slecture in English]] by Yu Wang   
***[[Bayes Parameter Estimation|Text slecture in English]] by Haiguang Wen <span style="color:GREEN">OK</span>
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==4. Local ("non-parametric") Density Estimation Methods==
***[[Bayersian Parameter Estimation: Gaussian Case|Text slecture in English]], by Shaobo Fang  
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*Introduction to Local density Estimation Techniques (so-called "non-parametric")  
***[[Bayes Parameter Estimation with examples|Text slecture in English]] by Yu Wang   
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**[[Introduction to local density estimation methods|Text slecture in English]] by Yu Liu
**Introduction to Local density Estimation Techniques (so-called "non-parametric")  
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**[[Slecture Introduction local density estimation methods ECE662 Spring2014 Aziza|Video slecture in Russian]] by Aziza Satkhozhina  
***[[Introduction to local density estimation methods|Text slecture in English]] by Yu Liu <span style="color:GREEN">OK</span>
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**[[Introduction to local density estimation methods ECE662 Spring2014 Nusaybah|Video slecture in English]] by Nusaybah Abu-Mulaweh  
***[[Slecture Introduction local density estimation methods ECE662 Spring2014 Aziza|Video slecture in Russian]] by Aziza Satkhozhina  
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**[[Intro local non parametric density estimation methods ECE662 Spring2014 Yuan|Video slecture in English]] by Chenxi Yuan
***[[Introduction to local density estimation methods ECE662 Spring2014 Nusaybah|Video slecture in English]] by Nusaybah Abu-Mulaweh  
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*Density Estimation with Parzen Windows  
***[[Intro local non parametric density estimation methods ECE662 Spring2014 Yuan|Video slecture in English]] by Chenxi Yuan <span style="color:GREEN">OK</span>
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**[[ParzenWindow|Text slecture in English]] by Chiho Choi
**Density Estimation with Parzen Windows  
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**[[Parzen Window Density Estimation|Text slecture in English]] by Ben Foster  
***[[ParzenWindow|Text slecture in English]] by Chiho Choi <span style="color:GREEN">OK</span>
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**[[Parzen Windows|Text slecture in English]] by Abdullah Alshaibani  
***[[Parzen Window Density Estimation|Text slecture in English]] by Ben Foster <span style="color:GREEN">OK</span>
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*Density Estimation with K-Nearest Neighbors (KNN)  
***[[Parzen Windows|Text slecture in English]] by Abdullah Alshaibani <span style="color:GREEN">OK</span>
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**[[KnnDensityEstimation|Text slecture in English]] by Raj Praveen Selvaraj  
**Density Estimation with K-Nearest Neighbors (KNN)  
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**[[Knearestneighbors|Text slecture in English]] by Dan Barrett
***[[KnnDensityEstimation|Text slecture in English]] by Raj Praveen Selvaraj <span style="color:GREEN">OK</span>
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**[[K-Nearest Neighbors Density Estimation|Video slecture in English]] by Qi Wang
***[[Knearestneighbors|Text slecture in English]] by Dan Barrett QUESTION PAGE
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*The Nearest Neighbor Decision Rule  
***[[K-Nearest Neighbors Density Estimation|Video slecture in English]] by Qi Wang <span style="color:GREEN">OK</span>
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**[[Estimation Using Nearest Neighbor|Text slecture in English]] by Sang Ho Yoon
**The Nearest Neighbor Decision Rule  
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**[[Slecture from KNN to nearest neighbor|Text slecture in English]] by Jonathan Manring  
***[[Estimation Using Nearest Neighbor|Text slecture in English]] by Sang Ho Yoon
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==5. Linear Classifiers ==
***[[Slecture from KNN to nearest neighbor|Text slecture in English]] by Jonathan Manring <span style="color:GREEN">OK</span>
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*Linear classifiers, projective coordinates, and Fisher linear discriminant
*Slectures on Linear Classifiers
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**[[JMSLinearClassifierSlecture|Text slecture in English]] by John Mulcahy-Stanislawczyk  
 
**[[JMSLinearClassifierSlecture|Text slecture in English]] by John Mulcahy-Stanislawczyk  
 
**[[CBR_logistic_regression|Text slecture in English]] by Borui Chen
 
**[[CBR_logistic_regression|Text slecture in English]] by Borui Chen
*Slectures on Support Vector Machines (SVM)  
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*Support Vector Machines (SVM)  
**[https://kiwi.ecn.purdue.edu/rhea/index.php/Least_Squares_Support_Vector_Machine_and_its_Applications_in_Solving_Linear_Regression_Problems Text slecture in English] by Xing Liu  
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**[[Least_Squares_Support_Vector_Machine_and_its_Applications_in_Solving_Linear_Regression_Problems| Text slecture in English]] by Xing Liu  
 
**[[Support Vector Machine|Video slecture in English]] by Tao Jiang  
 
**[[Support Vector Machine|Video slecture in English]] by Tao Jiang  
*Slectures on Clustering Algorithms (supplemental material)
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==6. Supplementary Material==
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*Clustering Algorithms  
 
**[[SlectureDavidRunyanCS662Spring14|text slecture in English]] by David Runyan
 
**[[SlectureDavidRunyanCS662Spring14|text slecture in English]] by David Runyan
 
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Latest revision as of 10:38, 22 January 2015


The Boutin Lectures on Statistical Pattern Recognition

Multilingual Slectures by Students in the Spring 2014 Class of ECE662


0. Foreword by Professor Boutin

1. Background Material

2. Bayes Rule

3. Global (parametric) Density Estimation Methods

4. Local ("non-parametric") Density Estimation Methods

5. Linear Classifiers

6. Supplementary Material


Go to ECE662 Spring 2014 Course Wiki

Go to Slecture Page

Alumni Liaison

Correspondence Chess Grandmaster and Purdue Alumni

Prof. Dan Fleetwood