| Line 64: | Line 64: | ||
*Slectures on Neyman-Pearson test and ROC curves | *Slectures on Neyman-Pearson test and ROC curves | ||
**[[Neyman-Pearson Lemma and Receiver Operating Characteristic Curve]] by [https://engineering.purdue.edu/~lee714/ Soonam Lee] | **[[Neyman-Pearson Lemma and Receiver Operating Characteristic Curve]] by [https://engineering.purdue.edu/~lee714/ Soonam Lee] | ||
| − | **[[ROC_curve_analysis_slecture_ECE662_Spring0214_Sun| | + | **[[ROC_curve_analysis_slecture_ECE662_Spring0214_Sun|ROC Curve and Analysis]] by Jianxin Sun |
*Slectures on Density Estimation | *Slectures on Density Estimation | ||
**Maximum Likelihood Estimation (MLE) | **Maximum Likelihood Estimation (MLE) | ||
Revision as of 09:03, 29 April 2014
Contents
ECE662: Statistical Pattern Recognition and Decision Making Processes, Spring 2014 (cross-listed with CS662)
Welcome to ECE662!
- HW2 grades have been entered into the "instructor's Comment" box.
- Reviews for HW2 are activated. Please complete your review before class on Tuesday April 29.
- Does anybody in the class speak Spanish (besides Francis)? If so, please send me an email. -pm
- Does anybody in the class speak Russian (besides Aziza)? If so, please send me an email. -pm
Course Information
Instructor:
- Office: MSEE342
- Office hours
- Assignment Drop Box
Lecture:
- When? TuTh, 10:30 - 11:45
- Where? EE117 (subject to change)
Slectures
Please use this template for text slectures or this template for video slectures
- Slectures on Probability and Statistics
- Whitening and Coloring Transforms, by Maliha Hossain
- How to generate n-D Gaussian data in the two category case , by Minwoong Kim (in Korean)
- Principal Component Analysis (PCA), by Tian Zhou
- Basics & examples of PCA, by Sujin Jang
- Slectures on Curse of Dimensionality
- Text slecture in English, and in Chinese by Haonan Yu
- Slectures on Bayes Rule
- Bayes Rule in Layman's Terms
- Link to page here
- Derivation of Bayes Rule
- Text slecture in English by Varun Vasudevan
- Video slecture in English by Nadra Guizani
- Video slecture in English by Jieun Kim
- Text slecture in Greek by Stylianos Chatzidakis
- Text slecture in English by Varun Vasudevan
- Bayes Rule for Normally distributed Features
- Text slecture in English by Jihwan Lee
- Upper Bounds for Bayes Error
- Text slecture in English by G. M. Dilshan Godaliyadda
- Text slecture in English by Yihan Ding PLEASE FOLLOW TEMPLATE
- Text slecture in English (includes the derivation of Chernoff Distance) by Jeehyun Choe
- Bayes Rule to Minimize Risk
- Video slectures in English, by Andy Park
- Text slecture in English by Dennis Lee
- Bayes rule in practice by Lu Wang
- Bayes Rule in Layman's Terms
- Slectures on Neyman-Pearson test and ROC curves
- Slectures on Density Estimation
- Maximum Likelihood Estimation (MLE)
- Text slecture in English by Sudhir Kylasa
- Text slecture in English by Hariharan Seshadri
- Expected Value and Deviation of Maximum LIkelihood Estimates over Multiple Trials by Spencer Carver
- Text slecture in English by Lu Zhang
- Introduction to Maximum likelihood estimate by Anantha Raghuraman
- Bayesian Estimation (BPE)
- Text slecture in English by Haiguang Wen
- Text slecture in English, by Shaobo Fang
- Introduction to Local density Estimation Techniques (so-called "non-parametric")
- Text slecture in English by Yu Liu
- Video slecture in Russian by Aziza Satkhozhina
- Density Estimation with Parzen Windows
- Text slecture in English by Chiho Choi
- Text slecture in English by Ben Foster
- Link here
- Density Estimation with K-Nearest Neighbors (KNN)
- Link here
- The Nearest Neighbor Decision Rule
- Text slecture in English by Sang Ho Yoon
- Maximum Likelihood Estimation (MLE)
- Slectures on Linear Classifiers
- SVM by Xing Liu
Peer Reviews
- Instruction for peer reviewing HW1
- Instruction for peer reviewing HW2 (due before class on April 29)
Discussion
Feel free to use the space below for discussion, or create a page for discussion and link it below.
- Where to find data for HW1
- Possible Real-world data to use for class
- Programming help!
- New Discussion
