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| Авторизация |
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| Jain A.K., Dubes R.C. — Algorithms for clustering data |
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| Предметный указатель |
Computer sampling 155 156 159
Computer vision 224
Conceptual clustering 92 224
Concordant pairs 153 154 167
Confidence bounds in Monte Carlo sampling 157
Confidence intervals, in bootstrapping 160
Confidence intervals, in Monte Carlo analysis 157
Connected graph 269
Connectivity test for randomness 221
Conover, W. J. 16 144 157 212
Contingency table for external indices of partitional adequacy 172
Contingency table for indicator functions 173
Contingency table for matching coefficients 16
Continuous feature 12
Continuous proximity index 12
Convergence, clustering algorithm 99
Conversion, between data scales 14
Conversion, between pattern and proximity matrices 11
Convex hull 207
Cooley, W, W. 81 179 264
Cooper, I. C. 139 153 177 185 188
Cophenetic correlation coefficient 166
Cophenetic matrix, and imposed structure 66
Cophenetic matrix, and tied proximities 68
Cophenetic matrix, and ultrametric inequality 84
Cophenetic matrix, of basal taxonomies 170
Cophenetic matrix, with external index 166
Cophenetic matrix, with Goodman - Kruskal  statistic 153
Cophenetic proximity and global fit of hierarchy 167
Cophenetic proximity and ultrametric inequality 69
Cophenetic proximity, and CPCC 166
Cophenetic proximity, definition 67
Cormack, R. 6 39
Cornelius, E. 53
Corrected statistic, for chance 175
Correlation between sequences 155
Correlation coefficient, rank 153
Correlation coefficient, rank, sample 16
Correlation matrix, sample 25
Correlation, point serial 148
Covariance function, spatial point process 212
Covariance matrix, in Gaussian density 247
Covariance matrix, in rotated coordinates 253
Covariance matrix, Lewis statistic 219
Covariance matrix, sample 25
Cox, D, R. 203 211
Cox, T. F. 218 219
CPCC 166
Cramer, H 247
Criterion, compared to index 161
Critical region, in hypothesis testing 146-47
Critical region, in Monte Carlo analysis 158
Cross, G. R. 213 217 218
Crossover and centroid methods 84
Crossover and monotonicity in dendrograms 83
Crossover and nonmonotone clustering 81
Crude Monte Carlo estimate 155
Cunningham 139 167
Cunningham, J. P. 48 53
Cutting a dendrogram 59
Cycles in testing for randomness 221
DATA 80X see 80X data)
Data collection 136
Data representation 7-54
Data type and index of cluster validity 162
Data type and scale 8-14
DATA1 with CLUSTER program 110
DATA1 with FORGY program 103
DATA1, complete-link dendrogram for 74
DATA1, description of 29
DATA1, eigenvector projection for 31
DATA1, single-link dendrogram of 74
DATA2 with CLUSTER program 110
DATA2 with FORGY program 106
DATA2 with Sammon nonlinear projection 40
DATA2, complete-link dendrogram of 77
DATA2, description of 30
DATA2, eigenvector projection for 30
DATA2, single-link dendrogram of 76
David, F. N. 148
Davies - Bouldin index 185
Davies, D. L. 185
Davis, L. 228
Day, N. E. 117
Day, W. H. E. 79
DB statistic 186
Deak 1 159
Decision theory 147
Degree of quantization 12
Delattre 65 72
Delaunay tessellation 214
Delaunay triangulation 125
Dendrogram and recovered structure 65
Dendrogram, catting 65
Dendrogram, crossovers and monotonicity 83
Dendrogram, proximity 62 66
Dendrogram, threshold 62
Dendrogram, visual impact of 89
Density estimation 118
Devijver, P, A. 147 243
Dewdney, A. K. 2
Diaconis, P. 159 160
Diameter method 65
Diameter of subgraph 86
Dichotomous data 17
Diday, E. 6
Dietz, E. J. 153
Diggle, P. J. 158 202 203 211 212
Diggle, P. J., 218
Digital image 225
Dimensionality 145
Dimensionality and sample size 243
Dimensionality, intrinsic see Intrinsic dimensionality
Directed tree 123
Dirichlet tessellation 125
Discrete feature 12
Discrete proximity index 12
Discriminant analysis and category labels 1
Discriminant analysis and hypothesis testing 264
Discriminant analysis and pattern recognition 242
Discriminant analysis and projection 34
Discriminant surface 57
Disjoint clustering 72
Dissimilarity 14
Dissimilarity, as proximity index 11
Dissimilarity, from discordant pairs 153-54 167
Distance methods, tests for randomness 217
Distribution, by bootstrapping 159
Distribution, Gaussian 246
Distribution, hypergeometric 249
Distribution, null 146
Distribution, two points in hypersphere 213
Divide and conquer 3
Divisive algorithm 57
Dixon, P. J. 19 20
Dubes, R. C. 6 23 96 97 101 108 137 138 159 176 177 189 195 200 202 207 217 218 219 220 221 223 224 238 243
Duda, R. O. 3 95 117 118 120 147 177 229 242 243 274
Dunn, J. C. 131
Duran, B. S. 5
Dynamic programming 91
Edelbrock, C. 139
Edelsbrunner, H. 79
Edge connectivity 86
Edge correction to sampling window 207
Edge detection 233
Edge effects on Cox - Lewis statistic 221
Edie, J. 119
Edwards, A. W. F. 91
Efron, B. 159 160
Eigen, D. J. 119
| Eigenvalue and number of features 27
Eigenvalue of sample covariance matrix 252
Eigenvalue, in range image segmentation 233
Eigenvalue, of covariance matrix 26
Eigenvector of invariance matrix 26 249
Eigenvector of sample covariance matrix 252
Eigenvector projection 26
Eigenvector transformation 27
Eigenvector with scatter matrices 95
Eigenvector, as basis vector 34
Eisenstein, B. A. 123
Elbow rule in MDSCAL 51
Ellipse of concentration 249
Embedding problem 48
Engelman, L. 179
Enslein, K. 6
entropy 45
ERDAS system 237
Erdos, P. 221
Error estimation 243
Esteva, J. C. 240
Estimation by bootstrapping 159
Euclidean distance 15
Evans, F. 217
Everitt, B. S. 1 5 16 38 59 141 177
Exclusive classification 56
Exploratory data analysis 4 135
External criterion for comparing hierarchical clusterings 170
External criterion, for validating clustering structures 161
External index for comparing two partitions 174
External index for estimating number of dusters 177
External index for global fit of hierarchies 166
External index for validity of individual clusters 189-92
External index of partitional adequacy 172
External index, in clustering methodology 137
External measures of validity in comparative analysis 140
Extrinsic classification 56
F-distribution 264
F-ratio 102-3
Factor analysis 260-63
Factor loading 260 262
Farris, J. S. 167
Feature 8
Feature average 24
Feature selection 243
Feature types 12
Feature variance 24
Features, imcorrelated 26
Fehlauer, J 123
Ferguson, T. S. 242
Fillenbaum, S. 221
Fisher, D. R. 166
Fisher, L. 138 139
Fisher, R. A. 215
Fishman, G. S. 159
Forcing pass 97
FORGY program, example 103-108
FORGY program, explanation 101
FORGY program, method 97
Forgy, E. 97 101
Fortier, J. J. 34 91
Foutz, R. V. 158
Fowlkes and Mallows statistic 174
Fowlkes, E. B. 140 170 174 175
Fractal dimensionality 43
Frame method for nonlinear projection 40
Freedman, D. A. 160
Friedman - Rafsky test 255
Friedman, H. P. 34 94 97 108
Friedman, J. H. 42 59 214
Frieze. A. 100
Fu. K. S. 128 129 223 224 226 243
Fukunaga, K. 3 34 37 45 243
Funk, G. M. 214
Fuzzy clustering 130
Fuzzy clustering and exclusive classification 56
Fuzzy clustering and partitionai clustering 94
Fuzzy sets 131
Gabriel graph 123-24
Gamma ( ) statistic see Hubert’s statistic
Garland, K. 223
Gaussian cluster 208
Gaussian density function 247
Gaussian distribution 246
Gelsema, E. S. 135
Geographic variation 153
Geometric interpretation, arithmetic averaging methods 80
Geometric structures 120
Geometrical pattern recognition 241
Gestalt principle 121
Gibbs process 211
Gitman 1 119 131
Global clustering criterion 90-92
Global fit for hierarchies 165
Global minimum in MDSCAL 52
Global structure 41
Global structure and MDSCAL 51
Globular cluster 95
Globular structure 129
Gnanadesikan, R. 137
Goidberg 119 235
Golden, R. R. 138
Goldstein 34 242
Golledge, R. G. 153
Gong, G. 160
Gonzalez, R. C. 224 243
Good man - Kruskal gamma () statistic 153
Good man - Kruskal gamma () statistic and monotone transformation 155
Good man - Kruskal gamma () statistic and validity of hierarchy 166
Good man - Kruskal gamma () statistic, example 154
Good man - Kruskal gamma () statistic, percentage points under random graph hypothesis 167
Good, J, J 4
Goodall, D. W. 20
Goodman, L. A. 16 153
Gordon, A. D 6 93 94 100
Gose, E. E. 119
Gowda, E. C. 92 129 130 235
Gower, J. 11 15 17 71 138
Grade of membership 131
Gradient descent procedure 40
Gradient descent procedure, in maximum likelihood estimation 118
Gradient descent procedure, in MDSCAL 50
Graph 266
Graph theory and hierarchical clustering 86
Graph theory and partitional clustering 120
Green, P. E. 47 252
Greig - Smith, P. 212
Griffith, D. A. 207 220
Gross, A. L. 139
Group average method 80
Hall, A. V. 17 24
Hall, D. J. 98 117
Hamdan, M. A. 20
Hammersley, J. 44 155 159 213
Hamming distance 15 92
Handscomb, D. C. 155 159
Hansen, P. 65 72
Hard spheres 208
Hard-core models 211
Harman, H. H. 260
Hart, P. E. 3 95 117 118 120
Hart, P. E., 147 177 229 242 243 274
Hart, R. E. 52
Hartigan, J. A. 5 38 59 134 138 141 179 182
Hawkins, D. 6
Henderson, J. 93 94 100
Heterogeneity function 17
Heydom, R. P. 34
Hierarchical clustering 58-88
Hierarchical clustering algorithms, definition 86
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