Principles of Statistical Machine Learning
Introduction to Nearest Neighbors Learning
Professor of Statistics
To understand God’s thoughts, one must study statistics, the measure of His purpose
Florence Nightingale
Nearest Neighbors Learning Machines
,The Two Greatest Commandments
30 · · ·
... and you shall love the Lord your God with all your heart and
with all your soul and with all your mind and with all your strength.
31 The second is this: Love your neighbor as yourself. No other
commandment is greater than these.
Mark 12:30
Nearest Neighbors Learning Machines
,Learning Objectives
1 Achieve a foundational knowledge of practical nearest neighbors
classification learning
2 Discover and learn practical nearest neighbors regression learning
3 Understand the central role of similarity/proximity and
dissimilarity measures in statistical machine learning
4 Dissect the most foundational properties of nearest neighbors
learning machines
5 Explore and comprehend the strength and limitations of the
Nearest Neighbors Learning paradigm
6 Apply nearest neighbors learning machines to practical problems
7 Read articles on applications of nearest neighbors learning
Nearest Neighbors Learning Machines
, Prerequisites and Tools
Prerequisites
1 Understanding the basics of conditional probability
2 Understanding indicator functions and summation notation
3 Understanding of distances and metrics
4 Basic knowledge of real analysis or advanced calculus
5 Solid acquaintance with R and Rstudio from previous lectures
Tools
1 library(caret)
2 library(MASS)
3 library(class)
4 library(FNN)
5 knn(x,xnew,y,k,...)
Nearest Neighbors Learning Machines
Introduction to Nearest Neighbors Learning
Professor of Statistics
To understand God’s thoughts, one must study statistics, the measure of His purpose
Florence Nightingale
Nearest Neighbors Learning Machines
,The Two Greatest Commandments
30 · · ·
... and you shall love the Lord your God with all your heart and
with all your soul and with all your mind and with all your strength.
31 The second is this: Love your neighbor as yourself. No other
commandment is greater than these.
Mark 12:30
Nearest Neighbors Learning Machines
,Learning Objectives
1 Achieve a foundational knowledge of practical nearest neighbors
classification learning
2 Discover and learn practical nearest neighbors regression learning
3 Understand the central role of similarity/proximity and
dissimilarity measures in statistical machine learning
4 Dissect the most foundational properties of nearest neighbors
learning machines
5 Explore and comprehend the strength and limitations of the
Nearest Neighbors Learning paradigm
6 Apply nearest neighbors learning machines to practical problems
7 Read articles on applications of nearest neighbors learning
Nearest Neighbors Learning Machines
, Prerequisites and Tools
Prerequisites
1 Understanding the basics of conditional probability
2 Understanding indicator functions and summation notation
3 Understanding of distances and metrics
4 Basic knowledge of real analysis or advanced calculus
5 Solid acquaintance with R and Rstudio from previous lectures
Tools
1 library(caret)
2 library(MASS)
3 library(class)
4 library(FNN)
5 knn(x,xnew,y,k,...)
Nearest Neighbors Learning Machines
