● Organisational Matters
● k-Nearest Neighbour
Distance is the Essential Ingredient
Inductive Bias
Extensions of k-Nearest Neighbour
● Probability Theory
● Naive Bayes
Problem Estimating Probabilities
Solution: Independence Assumption
Instructor: Tim van Erven (Tim.van.Erven@cwi.nl)
Website: www.cwi.nl/˜erven/teaching/0708/ml/
November 14, 2007
, Overview
Organisational
Matters
● Organisational Matters
k-Nearest Neighbour ● k-Nearest Neighbour
Distance is the
Essential Ingredient
✦ Distance is the Essential Ingredient
Inductive Bias
✦ Inductive Bias
Extensions of ✦ Extensions of k-Nearest Neighbour
k-Nearest Neighbour
Probability Theory
● Probability Theory
Naive Bayes
● Naive Bayes
Problem Estimating
Probabilities
✦ Problem Estimating Probabilities
Solution:
✦ Solution: Independence Assumption
Independence
Assumption
, Rescheduling
Organisational
Matters Guest Lecture:
k-Nearest Neighbour ● Peter Grünwald will give a special guest lecture about
Distance is the
Essential Ingredient
Minimum Description Length learning on December 5.
Inductive Bias
● This is an extra lecture to compensate for the lecture we
Extensions of missed because of my illness.
k-Nearest Neighbour
● (There was supposed to be no lecture on December 5,
Probability Theory
because I will be away to a conference.)
Naive Bayes
Problem Estimating
Probabilities
Solution:
Independence
Assumption
, Rescheduling
Organisational
Matters Guest Lecture:
k-Nearest Neighbour ● Peter Grünwald will give a special guest lecture about
Distance is the
Essential Ingredient
Minimum Description Length learning on December 5.
Inductive Bias
● This is an extra lecture to compensate for the lecture we
Extensions of missed because of my illness.
k-Nearest Neighbour
● (There was supposed to be no lecture on December 5,
Probability Theory
because I will be away to a conference.)
Naive Bayes
Problem Estimating Practical:
Probabilities
Solution: ● Homework exercises 6 will be the practical.
Independence
Assumption ● Will be intruced next lecture.
● Will be available after the lecture (one week earlier than
scheduled).
● This gives you two weeks to complete them.
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