Nils J. Nilsson - Introduction to Machine Learning.pdf

INTR ODUCTION
TO
MA CHINE LEARNING
AN EARL Y DRAFT OF A PR OPOSED
TEXTBOOK
Nils J
Nilsson
Rob otics Lab oratory
Departmen t puter Science
Stanford Univ ersit y
Stanford
CA
e
mail
nilsson
cs
stanford
edu
Septem b er
c
Cop yrigh t
Nils J
Nilsson
This material ma y not b e copied
repro duced
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written p ermission of the cop yrigh t holder
It is b eing made a v ailable on
the w orld
wide w eb in draft form to studen ts
facult y
and researc hers
solely for the purp ose of preliminary ev aluation
Con ten ts
Preliminar ies

In tro duction

What is Mac hine Learning

W ellsprings of Mac hine Learning

V arieties of Mac hine Learning

Learning Input
Output F unctions

T yp es of Learning

Input V ectors

Outputs

T raining Regimes

Noise

P erformance Ev aluation

Learning Requires Bias

Sample Applications

Sources

Bibliographical and Historical Remarks

Bo olean F unctions

Represen tation

Bo olean Algebra

Diagramm a tic Represen tations
unctions

Classes of Bo olean F

T erms and Clauses

DNF F unctions
i
CNF F unctions

Decision Lists

Symmetric and V oting F unctions

Linearly Separable F unctions

Summary

Bibliographical and Historical Rem