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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 |
80X data, description 8
80X data, discriminant analysis 36
80X data, eigenvector projection 28
80X data, examples of internal and external indices 162
80X data, factor analysis 28
80X data, first two principal components 28
80X data, listing 10
80X data, Sammon’s nonlinear projection 39
A priori information and external criteria 161
A priori labeling 153
A priori structure 148
Admissibility criteria 138
Affinity function 132
Agglomerative hierarchical clustering 59
Agglomerative scheme 72
Agrawala, A. K. 224
Ahuja, N. 125 128
Alagar, V. S. 44 213
Algorithm for bootstrap parameter estimation 160
Algorithm for generating clustered data 274
Algorithm, agglomerative 57
Algorithm, agglomerative, complete-link clustering 61
Algorithm, agglomerative, single-link clustering 61
Algorithm, baseline distribution, of  under random graph hypothesis 168
Algorithm, baseline distribution, of external index for partitional adequacy 176
Algorithm, baseline distribution, of internal index 165
Algorithm, complete-link method 63
Algorithm, complete-link, Johnson’s 72
Algorithm, divisive 57
Algorithm, divisive, single-link 70
Algorithm, fuzzy partitional clustering 133
Algorithm, iterative, partitional clustering 96
Algorithm, Monte Carlo estimation by binomial sampling 156
Algorithm, MST-based test of clustering tendency 214
Algorithm, multidimensional scaling 47
Algorithm, mutual neighborhood clustering 129
Algorithm, nearest neighbor clustering 128
Algorithm, Neyman - Scott process 208
Algorithm, options, hierarchical clustering 57
Algorithm, Prim’s for MST 271
Algorithm, projection 25
Algorithm, projection pursuit 42
Algorithm, relation to clustering method 58
Algorithm, SAHN 57
Algorithm, single-link clustering from graph theory 70
Algorithm, single-link method 63
Algorithm, single-link, Johnson’s 72
Algorithm, Zahn’s clustering 121
ALSCAL 53
Alternative hypothesis, aggregation 203 207
Alternative hypothesis, aggregation, regularity 208
Analysis of variance 179
Anderberg, M. R. 5 12 14 16 17 74 86 96 97 134 138
Ando 37
Andrews plots 136
Andrews representation 38
Andrews, D. F. 38 228
Andrews, H. C. 45
Arabie, P. 56 172 175
Arbitrary taxonomy 170
Archetypes 39
artificial intelligence 224
Atkinson, A. C. 159
Average distance 20
Average error 178
Average square-error 33
Average-link clustering, comparative analysis 138
Backer, E. 132
Bailey, D. E. 5
Bailey. T. A. 189 195 198
Baker, F. B. 72 141 167 170 193 221
Ball, G. H. 98 247 254
Ballard, D. H. 224 227 232 238 240
Barrow, H. G. 232
Bartels, P. H. 17
Barton, D. E. 148
Barycentric transformation 45
Basal taxonomies 170
Baseline distribution for external indices of partitional adequacy 175
Baseline distribution for Fowlkes and Mallows statistic 175
Baseline distribution for Hubert’s  statistic, example 163
Baseline distribution for index of cluster validity 161
Baseline distribution for internal and external indices 164
Baseline distribution for Jaccard coefficient 21
Baseline distribution for permutation statistic 23
Baseline distribution for simple matching coefficient 21
Baseline distribution for square-error 178
Baseline distribution, for CPCC 167
Baseline distribution, in Monte Carlo analysis 158
Baseline distribution, in test for nonrandom structure 162
Baseline population, in cluster validity 161
Baseline population, in cluster validity with random graph hypothesis 145
Baseline population, in cluster validity with random label hypothesis 145
Baseline population, in cluster validity, in testing hypotheses 144
Basis vector 32
Basis vector, Try clustering 134
Basu, J. P. 117
Bayne, N. K. 139
Bellman, R. E. 131
Bennett, R. S. 44
Bentler, P. 53
Besag, J. E. 158
Best-case compactness index 194
Best-case isolation index 194
Best-case method 192
Between-cluster scatter matrix 94
Between-group scatter matrix 259
Between-group similarities 4
Bezdek, J. 131 132
Bias in decision rules, bootstrapping 160
Bickel, P. J. 160
Binary features 12
Binary proximity index 12
Binary relation 60
Binary relation from threshold graph 60
Binary taxonomy 170
Binder, D. A. 118
Binomial coefficient 21 250
Binomial distribution 157
Binomial distribution, Monte Carlo sampling 156
Binomial sampling in Monte Carlo analysis 155 157
Binomial sampling m Poisson process 203
Biswas, G. 40 41
Blashfield, R. K. 134 139
Blashfield, R. K., 140
Blurring of critical region 158
Bock, H. H. 179 182
Bootstrapping 159-161
Botryology 4
Bouldin, D. W. 185
Boundaries, fuzzy 131
Box test 264
Brockett, P. L. 20
Brown C. M. 224 227 232 238 240
Brown T. 214
Bryant, J. 235
Buffer zone 220
Busk, P. 53
Caelli 53
Calhoun distance 17
Calvert, O. W. 37 42
Carlton, S. 228
Carmichael, J. W. 24
Carmone, F. J. 47
Carroll, J. D. 42 47 52 252
Categorical information 8
Category information, and linear projections 26
Category information, and nonlinear projections 37
Category information, with external criteria 161
Category labels and baseline distribution of external index 176
| Category labels and cluster analysis 1
Category labels and discriminant analysis 26 35
Category labels and external indices of partitional structure 172
Category labels and Hubert’s statistic 148 151
Category labels and internal index of partitional structure 177
Category labels and intrinsic classification 56
Category labels, DATA 1 30
Category labels, in FORGY 102
Cavalli - Sforza, L. L. 91
Central limit theorem 157
Centroid method 80
Centroid method, non monotone property 85
Centroid of cluster 94
Chained structures 129
Chained taxonomy 170
Chaining, singie-link dendrogram 75
Chandrasekaran, B. 243
Chang, C. L. 40
Chang, W. C. 29
Channel-filtering model 227
Characteristic function for partition 18
Chebychev inequality 157
Chemick, M. R. 160
Chemoff, H. 37 38
Chen, H. J. 223
Chen, N. K. 45
Cheng, Y. 224
Chernoff faces 37 136
Chhikara, R. S. 119
Chi-square statistic 213
Chien, Y. 38
Cigar-shaped data 108
City block distance 15
Clark, P. 217
Classification 55
Clifford, H. 5 57
CLIQUE 270
Clique and complete-link clustering 61 63 65
CLUSTAN 134
Cluster analysis, definition 1
Cluster analysis, difference from pattern recognition 241
Cluster analysis, packages 134
Cluster applications 223-240
Cluster axiomatic basis 138
Cluster center 93
Cluster label and clustering methods 14
Cluster label and F-distribution 103
Cluster label and intrinsic classification 57
Cluster label with SOX data 163-64
Cluster membership function 132
Cluster profile, as plots 195
Cluster profile, definition 191
Cluster profile, examples 191 92
CLUSTER program and DATA 2 111
CLUSTER program, DATA 1
CLUSTER program, description 108
CLUSTER program, effect of dimensionality 178
CLUSTER program, effect of number of clusters 178
CLUSTER program, in range image segmentation 233
Cluster shape 91
Cluster shape, prior knowledge 123
Cluster validation 143
Cluster validity 143-222
Cluster validity of individual clusters 188-201
Cluster validity, in hierarchical structures 165-72
Cluster validity, in image segmentation 228
Cluster validity, in partitional structures 172-88
Cluster validity, indices 160
Cluster validity, statistical tools for 161
Cluster, (k,r) 88
Cluster, as collection of patterns 8
Cluster, cigar-shaped 29
Cluster, crisp 131
Cluster, definitions 1
Cluster, description 161
Cluster, fuzzy 131
Cluster, lifetime 197 198
Cluster, line-like 122
Cluster, non-homogeneous 122
Cluster, touching 122
Cluster-by-category table, eightyX data 162
Clustering algorithm and clustering method 96 134
Clustering and decision making 4
Clustering criterion, determinant of scatter matrix 95
Clustering criterion, from scatter matrices 95
Clustering criterion, global 90
Clustering criterion, in partitional clustering 90
Clustering criterion, local 90
Clustering method 55-142
Clustering method and clustering algorithm 96
Clustering method for image registration 240
Clustering method, difference from clustering algorithm 134
Clustering method, square-error 96
Clustering method, to group pixeis 226
Clustering methodology 135 41
Clustering of pixels in spectral domain 235
Clustering packages 133
Clustering software 133-35
Clustering strategy 137
Clustering structure and a priori structure 148
Clustering structure, adequacy of 160
Clustering structure, criteria for 161
Clustering structure, unusualness of 143
Clustering structure, validation by bootstrapping 159
Clustering structure, validity of 146
Clustering tendency 201-222
Clustering tendency, in clustering methodology 136
Clustering, by cutting a dendrogram 59
Clustering, by density estimation 118
Clustering, by graph theory 120
Clustering, by mixture decomposition 117
Clustering, conceptual 92
Clustering, hierarchical 58-89
Clustering, nearest neighbor 128
Clustering, partitional 89-133
Clustering, space-time 148
CM-reachabic method 192
Coggins, J. 227 228 231
Cohen, A. 223
Coleman, G. B. 228
Communality 261
Compact cluster 192
Compactness index of cluster, best-case 194
Compactness index of cluster, best-case, external 191
Compactness index of cluster, best-case, internal 192
Compactness of cluster and within-ciuster scatter matrix 95
Compactness of cluster, definition 189
Compactness of cluster, in duster vafidity 188-89
Comparative analysis 137
Comparison of algorithms in image segmentation 233
Complete graph 269
Complete spatial randomness 201
Complete-link algorithm, agglomerative 61
Complete-link algorithm, by matrix updating 79
Complete-link algorithm, from graph theory 60
Complete-link algorithm, Hubert’s 63
Complete-link algorithm, Johnson’s 72
Complete-link cluster, as clique 64
Complete-link cluster, visual assessment 75
Complete-link clustering and complete subgraphs 62
Complete-link clustering, comparative analysis 138
Complete-link clustering, in range image segmentation 233
Complete-link hierarchy and relative criteria 161
Complete-link method, characterization 65
Complete-link method, difference from single-link 74
Complete-link method, graph theory algorithms 70
Complete-link method, matrix updating 72
Complexity of K-means algorithms 100
Component densities 117
Computational complexity 3
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