Pattern analysis algorithms described in the book

Computations

Computation 2.5 Ridge regression 30
Computation 5.14 Regularised Fisher discriminant 131
Computation 5.15 Regularised kernel Fisher discriminant 133
Computation 6.3 Maximising variance 141
Computation 6.18 Maximising covariance 154
Computation 6.30 Canonical correlation analysis 163
Computation 6.32 Kernel CCA 165
Computation 6.34 Regularised CCA 169
Computation 6.35 Kernel regularised CCA 169
Computation 7.1 Smallest enclosing hypersphere 193
Computation 7.7 Soft minimal hypersphere 199
Computation 7.10 nu-soft minimal hypersphere 202
Computation 7.19 Hard margin SVM 209
Computation 7.28 1-norm soft margin SVM 216
Computation 7.36 2-norm soft margin SVM 223
Computation 7.40 Ridge regression optimisation 229
Computation 7.43 Quadratic e-insensitive SVR 231
Computation 7.46 Linear e-insensitive SVR 233
Computation 7.50 nu-SVR 235
Computation 8.8 Soft ranking 254
Computation 8.17 Cluster quality 261
Computation 8.19 Cluster optimisation strategy 265
Computation 8.25 Multiclass clustering 272
Computation 8.27 Relaxed multiclass clustering 273
Computation 8.30 Visualisation quality 277
440

Algorithms

Algorithm 5.1 Normalisation 110
Algorithm 5.3 Centering data 113
Algorithm 5.4 Simple novelty detection 116
Algorithm 5.6 Parzen based classifier 118
Algorithm 5.12 Cholesky decomposition or dual Gram´┐ŻSchmidt 126
Algorithm 5.13 Standardising data 128
Algorithm 5.16 Kernel Fisher discriminant 134
Algorithm 6.6 Primal PCA 143
Algorithm 6.13 Kernel PCA 148
Algorithm 6.16 Whitening 152
Algorithm 6.31 Primal CCA 164
Algorithm 6.36 Kernel CCA 171
Algorithm 6.39 Principal components regression 175
Algorithm 6.42 PLS feature extraction 179
Algorithm 6.45 Primal PLS 182
Algorithm 6.48 Kernel PLS 187
Algorithm 7.2 Samllest hypersphere enclosing data 194
Algorithm 7.8 Soft hypersphere minimisation 201
Algorithm 7.11 nu-soft minimal hypersphere 204
Algorithm 7.21 Hard margin SVM 211
Algorithm 7.26 Alternative hard margin SVM 214
Algorithm 7.29 1-norm soft margin SVM 218
Algorithm 7.32 nu-SVM 221
Algorithm 7.37 2-norm soft margin SVM 225
Algorithm 7.41 Kernel ridge regression 229
Algorithm 7.45 2-norm SVR 232
Algorithm 7.47 1-norm SVR 234
Algorithm 7.51 nu-support vector regression 236
Algorithm 7.52 Kernel perceptron 237
Algorithm 7.59 Kernel adatron 242
Algorithm 7.61 On-line SVR 244
Algorithm 8.9 nu-ranking 254
Algorithm 8.14 On-line ranking 257
Algorithm 8.22 Kernel k-means 269
Algorithm 8.29 MDS for kernel-embedded data 276
Algorithm 8.33 Data visualisation 280

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