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An Introduction to Support Vector Machines and Other Kernel-based Learning Methods by Nello Cristianini, John Shawe-Taylor

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Index

active set methods, 136

adaboost, 77

Adatron, 25, 134

affine function, 81

ANOVA kernels, 50

Bayes formula, 75

bias, 10, 130

bioinformatics, 157

box constraint algorithm, 108

capacity, 56

control, 56, 93, 112

chunking, 136

classification, 2, 9, 93

compression, 69, 100, 112

computational learning theory, 77

computer vision, 152

consistent hypothesis, 3, 54

constraint

active and inactive, 80

box, 107

equality and inequality, 80

convex

combination, 166

function, 80

hull, 89

programming, 81

set, 80

convex optimisation problem, 81

covariance matrix, 48

cover, 59

covering number, 59

curse of dimensionality, 28, 63

data dependent analysis, 58, 70, 78

decision function, 2

decomposition, 136

dimension

fat-shattering, see fat-shattering dimension ...

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