文档介绍：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
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It is b eing made a v ailable on
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wide w eb in draft form to studen ts
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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