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| Поиск по указателям |
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| Fukunaga K. — Introduction to Statistical Pattern Recognition |
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| Предметный указатель |
Absolute correction rule see Correction rule
Autocorrelation function 418
Autocorrelation matrix see Matrix
Autocorrelation mixture see Scatter matrix mixture
Bahadur expansion see Expansion
Basis function 287 385 417
Basis vector 401
Basis, complete set of 417
Bayes, classifier see Classifier
Bayes, conditional cost 57
Bayes, conditional error 52
Bayes, decision rule see Decision rule
Bayes, error see Error
Bayes, estimate see Successive Bayes estimation
Bayes, linear classifier see Linear classifier
Bayes, theorem 12 52
Beta distribution see Distribution
Bhattacharyya, bound 99
Bhattacharyya, distance see Distance
Bhattacharyya, estimate see Estimate
Binary input 173 290
Binary input, density function of 290
Binary input, discriminant function for 131
Binary input, orthonormality of 174 291
Binomial distribution see Distribution
bisector 128 444 517
Block toeplitz matrix see Matrix
Bootstrap 238
Bootstrap, bias 243
Bootstrap, error 240
Bootstrap, method 238
Bootstrap, samples 239
Bootstrap, variance 246
Branch and bound for nearest neighbor 361
Branch and bound, clustering 523
Branch and bound, feature subset selection 491
Branch and bound, feature subset selection, basic algorithm 494
Branch and bound, feature subset selection, improved algorithm 496
Burdick’s chart 63
Central limit theorem 17
Characteristic equation 26
Characteristic function 16 88
Characteristic function of likelihood ratio 88
Characteristic function of normal distribution 16 91
Chernoff bound 98
Chernoff distance see Distance
Chi-square distribution 83 see gamma
Circular error see Error
Class probability see Probability
Class separability see Separability
Classification 510
Classification supervised 51
Classification unsupervised 508
Classifier see also Decision rule
Classifier, correlation 125
Classifier, design 7
Classifier, distance 127
Classifier, linear see Linear classifier
Classifier, piecewise see Piecewise classifier
Classifier, quadratic see Quadratic classifier
Clustering 508
Clustering, algorithm 511
Clustering, criterion 510
Clustering, graph theoretic approach 539
Clustering, nearest local-mean reclassification rule see Nearest local-mean reclassification rule
Clustering, nearest mean reclassification rule see Nearest mean reclassification rule
Clustering, nonparametric approach 533
Clustering, normal decomposition see Normal decomposition
Clustering, parametric aproach 510
Clustering, valley-seeking 534 542
Colored noise 128
Column correlation coefficient 164
Condensed nearest neighbor see kNN
Configuration 510
Confusion matrix 518
Conjugate pair see Density function
Convergence for linearly separable case 153 371
Convergence in mean-square sense 381
Convergence of nearest mean reclassification rule see Nearest mean reclassification rule
Convergence of stochastic approximation 378
Convergence with probability 1 381
Convergence, acceleration of 388
Correction rule, absolute 369
Correction rule, fixed increment 369
Correction rule, gradient 369
Correlation 125
Correlation, classifier 15 see
Correlation, matrix see Matrix
Cost of decision 57
Cost, conditional 57
Cost, symmetrical 58
Covariance 14
Covariance function 418
Covariance matrix see Matrix
Coverage 255 269
Data compression 409
Data display, nonparametric 353
Data display, parametric 154
Data display, risk contour 355
Data filter 537
Data reduction, nonparametric 549
Data reduction, parametric 556
Decision rule, Bayes, for minimum error 51
Decision rule, Bayes, for minimum risk 57
Decision rule, likelihood ratio 52
Decision rule, minimax 61
Decision rule, Neyman — Pearson 59
Density function 12
Density function of binary inputs see Binary input
Density function of coverage 269
Density function of likelihood ratio 54
Density function, a posteriori 390
Density function, a priori 390
Density function, class 12
Density function, conditional 12
Density function, conjugate pair 392
Density function, estimate of k nearest neighbor approach see kNN
Density function, expansion of 287
Density function, exponential 56 70
Density function, gamma 23 69 573
Density function, gradient of 534
Density function, marginal 13
Density function, mixture 12
Density function, Parzen approach see Parzen
Density function, reproducing pair 392
Design sample see Sample
Desired output 145 147
Desired output, vector 149
Diagonal matrix see Matrix
Diagonalization 27
Diagonalization, simultaneous 31
Dimensionality 426
Dimensionality, intrinsic 280 537
Dimensionality, local see Dimensionality intrinsic
Directed, path 539
Directed, tree 539
Discriminant analysis 445
Discriminant analysis, nonparametric 466
Discriminant function 52
Discriminant function for binary inputs see Binary input
Discriminant function, desired output of see Desired output
Discriminant function, linear see Linear classifier
Discriminant function, piecewise see Piecewise classifier
Discriminant function, quadratic see Quadratic classifier
dispersion 13
Distance classifier see Classifier
Distance, between-sample 411
Distance, Bhattacharyya 99 188
Distance, Bhattacharyya, for feature extraction 455
Distance, Chernoff 98
| Distance, distribution of see Distribution
Distance, normalized 16
Distribution of distance 68
Distribution, Beta 75 270 573
Distribution, binomial 200
Distribution, function 11
Distribution, Gaussian — Wishart 393
Distribution, normal 16 573
Distribution, normal, characteristic function of 16
Distribution, normal, conditional density 48
Distribution, normal, entropy 412
Distribution, normal, generation of 30
Distribution, normal, likelihood ratio for 54
Distribution, normal, marginal density 48
Distribution, normal, probability of error for 91
Distribution, normal, test of see Normality test
Distribution, normal, Wishart 392
Distributional test 476
Divergence 458
Double exponential waveform 284 472
Edited k nearest neighbor see kNN
Effective dimensionality see Dimensionality intrinsic
Eigenfuhction 418
Eigenvalues 26
Eigenvalues of autocorrelation function 418
Eigenvalues, estimation of 431
Eigenvalues, matrix see Matrix
Eigenvalues, normalization of 410
Eigenvalues, perturbation of 426
Eigenvectors 27
Eigenvectors, estimation of 431
Eigenvectors, matrix see Matrix
Eigenvectors, perturbation of 426
entropy 412 550
Entropy for binary inputs 416
Entropy for normal distributions see Distribution normal
Entropy, maximization 413
Entropy, minimax 415
Entropy, minimization 416 550
Error of linear classifier 85
Error of quadratic classifier 91
Error, Bayes 53
Error, circular 287
Error, conditional 52
Error, control 351
Error, counting 197 200
Error, estimate 87 197
Error, function (normal) 63 576
Error, lower bound of 220 307
Error, mean-square 145 402
Error, pairwise 284
Error, probability of 52 85 87 197
Error, reject curve 79
Error, upper bound of 97 220 307
Estimate grouped error 356
Estimate of Bhattacharyya distance 18
Estimate of Bhattacharyya distance, bias 189 190
Estimate of Bhattacharyya distance, variance 189 190
Estimate of density function see Density function
Estimate of density gradient 534
Estimate of error 196 301 303 344
Estimate, Bayes (successive) see Successive Bayes estimation
Estimate, biased 21 183 187 259 272 313 326 347
Estimate, consistent 19 261 273
Estimate, k nearest neighbor density see kNN
Estimate, maximum likelihood see Normal decomposition
Estimate, moment see Moment
Estimate, Parzen density see Parzen
Estimate, sample see Sample
Estimate, unbiased 18
Estimate, variance 183 187
Expansion by basis functions see Basis
Expansion, Bahadur 292
Expansion, Karhunen — Loeve 403 417
Expansion, kernel of 287
Expansion, square error of 288
Expansion, Walsh 292
Expected for random process 418
Expected value 13
Expected vector 13
Factor analysis 417
Feature extraction for classification 442
Feature extraction for signal representation 400
Feature extraction, general critrion for 460
Feature extraction, sequential 480
Feature ideal 444
Feature selection see Feature extraction
Feature, space 402
Feature, subset selection 489
Feature, subset selection, backward selection 490
Feature, subset selection, branch and bound 491 see
Feature, subset selection, stepwise search technique 490
Feature, vector 402
Fisher, classifier see Linear classifier
Fisher, criterion 134
Fixed increment rule see Correction rule
Fourier transform for stational process 421
Fourier transform of likelihood ratio 159
Fourier transform, orthonormality of 156
Fourier transform, quadratic classifier of 159
Gamma, density see Density function
gamma, function 23 574 578
Gaussian pulse 282 472
Gaussian — Wishart distribution see Distribution
Goodness-of-fit see Chi-square
Gradient correction rule see Correction rule
Gradient of density function see Density function
Gradient, estimate of see Estimate
Graph theoretic clustering see Clustering
Grouped error estimate see Estimate
Harmonic sequence see Sequence
Hermite polynomial 288
Holdout method 220 310
Hughes phenomena 208
Hyperellipsoid, surface area 314 573
Hyperellipsoid, volume 260 572
Hypothesis test, composite 83
Hypothesis test, multi- 66
Hypothesis test, sequential see Sequential (hypothesis) test
Hypothesis test, simple 51
Hypothesis test, single 67
Intrinsic dimensionality see Dimensionality
Inverse matrix see Matrix
K nearest neighbor (NN) - volumetric 305
K nearest neighbor (NN) - volumetric, classification 303
K nearest neighbor (NN) - volumetric, classification, likelihood ratio for 303
K nearest neighbor (NN) - volumetric, density estimation 268 575
K nearest neighbor (NN) - volumetric, density estimation, bias 272
K nearest neighbor (NN) - volumetric, density estimation, consistent 273
K nearest neighbor (NN) - volumetric, density estimation, metric 275
K nearest neighbor (NN) - volumetric, density estimation, moments 270
K nearest neighbor (NN) - volumetric, density estimation, moments, approximation of 270
K nearest neighbor (NN) - volumetric, density estimation, optimal k 273
K nearest neighbor (NN) - volumetric, density estimation, optimal k, minimum IMSE 275
K nearest neighbor (NN) - volumetric, density estimation, optimal k, minimum MSE 214
K nearest neighbor (NN) - volumetric, density estimation, unbias 273
K nearest neighbor (NN) - volumetric, density estimation, variance 273
K nearest neighbor (NN) - volumetric, distance to kNN 277
K nearest neighbor (NN) - volumetric, distance to kNN, effect of parameters 278
K nearest neighbor (NN) - volumetric, error estimation, bias 347
K nearest neighbor (NN) - volumetric, error estimation, L estimate of a covariance 351
K nearest neighbor (NN) - volumetric, error estimation, leave-one-out method 303
K nearest neighbor (NN) - volumetric, error estimation, metric 303
K nearest neighbor (NN) - volumetric, error estimation, resubstitution method 303
K nearest neighbor (NN) - volumetric, progression 552
K nearest neighbor (NN), approach - voting 305
K nearest neighbor (NN), asymptotic conditional risk and error 307
K nearest neighbor (NN), asymptotic conditional risk and error, 2NN 306
K nearest neighbor (NN), asymptotic conditional risk and error, kNN 306
K nearest neighbor (NN), asymptotic conditional risk and error, multiclass 309
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