01-kNN.pdf

Outline
About This Course
Method of k-Nearest Neighbors
Chapter 1: Method of k-Nearest Neighbors
Jiangsheng Yu
School of Electronics Engineering puter Science
Peking University, Beijing 100871, China
Statistical Machine Learning, 2008
Jiangsheng Yu Method of k-Nearest Neighbors
Outline
About This Course
Method of k-Nearest Neighbors
Outline of topics
1 About This Course
Requirements and notifications
References of statistical machine learning
What is machine learning?
Machine learning, pattern recognition and data mining
Fonts and styles in this course
2 Method of k-Nearest Neighbors
Algorithm description
History of k-NN method
Metric space
Linear metric space
Normed space
Error estimation
Error estimation of 1-NN method
Error estimation of k-NN method
Jiangsheng Yu Method of k-Nearest Neighbors
2 Programming languages R (or S-PLUS), BUGS, etc.
3 UNIX-like operating systems, BSD family, GNU/Linux, etc.
4 Applications: bioinformatics, web information processing,
natural language processing, stock analysis, etc.
5 Score: homework w1 ∼ U[, ], midsemester
w2 ∼ U[, ] and final test 1 − w1 − w2.
6 Reasonable suggestions to the course are e. You may
send emails to ******@pku. or call 62765818.
7 The slides are freely available at ./yujs.
8 Teaching assistant: Zizhen Wang, wzzpku@
Outline Requirements and notifications
About This Course References of statistical machine learning
Method of k-Nearest Neighbors What is machine learning?
Requirements and notifications
1 The mathematics of statistical machine learning.
Jiangsheng Yu Method of k-Nearest Neighbors
3 UNIX-like operating systems, BSD family, GNU/Linux, etc.
4 Applications: bioinformatics, web information processing,
natural language processing, stock analysis, etc.
5 Score: homework w1 ∼ U[, ], midsemester
w2 ∼ U[, ] and final test 1 − w1 − w2.
6 Reasonable suggestions to the course are e. You