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Jain A.K., Dubes R.C. — Algorithms for clustering data
Jain A.K., Dubes R.C. — Algorithms for clustering data



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Название: Algorithms for clustering data

Авторы: Jain A.K., Dubes R.C.

Язык: en

Рубрика: Математика/Вероятность/Статистика и приложения/

Статус предметного указателя: Готов указатель с номерами страниц

ed2k: ed2k stats

Издание: 1

Год издания: 1988

Количество страниц: 320

Добавлена в каталог: 04.06.2005

Операции: Положить на полку | Скопировать ссылку для форума | Скопировать ID
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Предметный указатель
Hierarchical clustering and sequence of nested partitions      59
Hierarchical partition      57
Hierarchical structure and ultrametricity      68
Hierarchical structure, perfect      68
Hierarchical structure, true      69
Hierarchical tree classifier      243
hierarchies      160
Hill-climbing      91
Hill-climbing pass      97
Hines, R. J, O.      211
Hines, W. C. S.      211
Histogram of edge lengths in MST gray-level      225
Histogram of Hubert’s $\Gamma$ for 80X data      163
Histogram of nearest-neighbor distances      218
Histogram with Hubert’s $\Gamma$ statistic      149-50
Histogram, in density estimation      119
Histogram, shift in, from random label to random position hypotheses      165
Hoffman, R.      214 224 232 233 235
Hopkins statistic      218
Hopkins, B.      211 218
Hord, R      225 235
Hough transform      240
Howe, S. E.      125
Hubalek, Z.      17
Huber, P. J.      42
Hubert, L. J.      11 53 63 64 72 79 86 141 148 153 167 168 170 172 175 176 193 221
Hubert’s algorithm, for complete-link clustering      63
Hubert’s algorithm, for complete-link clustering for single-link clustering      63
Hubert’s gamma ($\Gamma$) statistic      148
Hubert’s gamma ($\Gamma$) statistic and degree oflinearcorrespondence      149
Hubert’s gamma ($\Gamma$) statistic and validity of hierarchy      166
Hubert’s gamma ($\Gamma$) statistic with stopping rule      185
Hubert’s gamma ($\Gamma$) statistic, 80X data, example      151
Hubert’s gamma ($\Gamma$) statistic, external criterion, example      162
Hubert’s gamma ($\Gamma$) statistic, in comparative analysis      140
Hubert’s gamma ($\Gamma$) statistic, in partitional adequacy      174
Hubert’s gamma ($\Gamma$) statistic, internal criterion, example      162
Hubert’s gamma ($\Gamma$) statistic, modification for relative index      186
Hubert’s gamma ($\Gamma$) statistic, normalized      148
Hypergeometric distribution      249
Hypergeometric distribution and external indices of cluster validity      189-90
Hypergeometric distribution and external indices of partitional adequacy      175
Hypergeometric distribution and permutation statistic      23
Hypergeometric distribution and probability profiles      195
Hypergeometric probability, computing      250
Hypergeometric probability, computing, Peizer approximation to      251
Hypersphere, distribution of distances in      44
Hypothesis, alternative      146 148
Hypothesis, alternative, null      144-47
Hypothesis, alternative, null, for Hubert’s gamma ($\Gamma$) statistic      149
Hypothesis, alternative, random graph      144 45 149
Hypothesis, alternative, random label      144 45 149
Hypothesis, alternative, random position      144-45
Hypothesis, alternative, randomness      144
Hypothesis, alternative, randomness, and internal index of partitional adequacy      179
Hypothesis, alternative, testing      144
ICICLE package      134
Identifiable mixture      117
Image classification      226
Image classification, image processing      224
Image registration      237
Image segmentation and clustering      225
Ince, F.      235
Inconsistent edges      121
Inconsistent edges and sparse clusters      123
Inconsistent edges and structure graphs      128
Inconsistent edges, in range image segmentation      233
Index of cluster validity      160-65
Index of partitional adequacy      174
Index of proximity      11
Index of structure      147
Index, compared to criterion      161
Index, for comparing partitions      172
Indicator function      173
INDSCAL program      53
Information measure for contingency table      20
Initial partition, in iterative partitional clustering      96
Initial partition, in square-error clustering      97
Initial partition, recovery from      98
Intensity of spatial point process      212
Internal edges, as compactness index      189-90
Internal edges, in best-case indices      194
Internal index for clusters      192
Internal index for global fit of hierarchies      166
Internal index of partitional adequacy      177
Internal index, as relative index of partitional adequacy      178
Internal index, in clustering methodology      137
Interpoint distance and test for randomness      213
Interpoint distance, in intrinsic dimensionality      45
Interval estimator      157
Interval scale      13
Intrinsic character of data      160
Intrinsic classification      56
Intrinsic dimensionality      42 46
Intrinsic dimensionality, Bennett’s method      44
Intrinsic dimensionality, estimation from near-neighbor information      46
Intrinsic dimensionality, global approach      44
Intrinsic dimensionality, in clustering methodology      136
Intrinsic dimensionality, local approach      45
Intrinsic dimensionality, Trunk’s method      46
Isaac, P. D.      139
Isham, V.      203 211
Ismail, M. A.      99
ISODATA, and nearest-neighbor computation      3
ISODATA, description      98
ISODATA, fuzzy      132
ISODATA, in remote sensing      237
ISODATA, parallel computation      101
Isolated cluster      192
Isolation index      189-90
Isolation index, best case      194
Isolation of cluster      188-90
ISPAHAN      135
Iterative partitional clustering algorithm      96
Ittner, D.      232
Jaccard coefficient      17
Jaccard coefficient for binary vectors      21
Jaccard statistic      174
Jain, A. K.      6 96 97 101 108 132 137 138 160 177 202 203 215 218 221 223 224 227 231 232 233 235 243 245 247
Jardine, N.      5 64 69 77 38
Jarvis, R. A.      129
Jensen, R. E.      91
Johnson, I. E.      159
Johnson, S. C.      65 72
Johnston, B.      133
Joins      214
Journal of classification      4
Julesz, B.      227
K - MEANS algorithm in comparative analysis      140
K - MEANS algorithm in comparative analysis, means method, implementation      134
K - MEANS algorithm in comparative analysis, means pass      97 109
Kak      224
Kakusho      53
Kamel      210
Kamenskii, V. S.      47
Kamgar - Parsi, B.      129
Kanal, L. N.      6 129
Karhunen - Loeve projection      26
Katz, J. O.      119
Kelly, F. P.      214
Kempthome, O.      23
Kendall, M. G.      56
Kendal’s $\tau$ statistic      167
Kernel function      120
Killough, G. S.      221 222
King, B.      72
Kirkpatrick, S.      39
Kittler, J.      19 91 119 120 147 243
Klahr, D      51
Kleiner, B.      38 59
Knee with eigenvector projection      27
Knee, in curve of average error      179
Knee, significant, in relative index of validity      187
Knoll, R. L.      51
Knuth, D. E.      159
Kolmogorov - Smirnov statistic      213
Koontz, W. L. G.      37 91 119 123 133
Korfhage, R. R      266
Krishna, G.      92 129 130
Krishnaiah, P. R.      6
Kruskal, J. B.      39 47 51 52
Kruskal, J. B.,      53
Kruskal’s stress      47
Kruskat, W. H.      16 153
Krzanowski, W. J.      27
Kuiper, F. K.      139
Lachenbruch, P. A.      34 242
Lance, G. N.      56 79 80 86
Landis, D.      53
LANDSAT image      235
Lane      120
Lattice regularity      208
Lee, D.      125
Lee, R.      6 40 41
Lefkovitch, L. P.      91
Legendre, P.      15
Lesaffre, E.      247
Level function      66
Level of significance in Monte Carlo analysis, J      58
Level of test of hypothesis      146
Level, critical      146
Levine, D. I., II      12 48 51 52
Levine, M. D.      119 131
Lewis      218 219
Li, X.      20 22 23 238 251
Liebetrau, A.      212
Lifetime of cluster      197-98
Light stripping      232
Likelihood function      211
Lindman, H.      53
Linear algebra      252-57
Linear dimensionality      43
Linear projection      25-36
Ling index      198
Ling, R. F.      87 88 145 197 221 222 250
Lingoes, J. C.      48
Linking edge, as isolation index      189-90
Linking edge, in best-case index      194
Liu, T. S.      119
Local clustering criterion      90
Local minimum in MDSCAL      52
Local minimum, effect of initial partition      97
Lohnes, P. R.      81 179 264
Lorr      5
Lu, S. Y.      128 129 223
Lumelsky, V.      24
MacCailum, R. C.      53
Machine vision      224
Magnuski, H. S.      123
Mahaianobis distance, definition      16
Mahaianobis distance, in Gaussian distribution      249
Mahaianobis distance, in square-error clustering      93
Mahtab, M. A.      223
Mallows, C. L.      140 170 174 175
Mandelbrot, A. B.      43
Manhattan distance      15
Manova      see Multivariate Analysis of Variance
Mantel statistic      148
Mantel statistic, E      53
Mantel, N.      148 153
Mantock, J.      37
Marriott, F. H. C.      138 158
Matching coefficient      16
Matrix updating algorithm      79
Matrix updating algorithm and monotonicity      79
Matrix updating algorithm, complete-link      72
Matrix updating algorithm, effect of ties      78
Matrix updating algorithm, example      73
Matrix updating algorithm, single-link      72
MatuJa, D. W.      65 123 200
Matula index      200
Maxima1 subgraph      64
Maximal complete subgraph      269
Maximizing scatter      34
Maximum method      65
McClain, J. O.      179
McLachlan, G. J.      117
McLaughlin, B.      139
McQueen, J. B.      97
McQueen’s K-means method      97
MDSCAL, algorithm      47
MDSCAL, algorithm and hierarchical clustering      52
MDSCAL, algorithm and Sammon’s nonlinear projection      39
MDSCAL, algorithm, interpreting configurations      51
MDSCAL, algorithm, naming axes      52
MDSCAL, algorithm, program      50
Mead, R.      212
Measurement space      2
Median method      80
Meehl, P. E.      138
Metropolis algorithm      212
Metropolis, N.      211
MH-Modified Hubert’s $\Gamma$ statistic      187
Michalski, R. S.      92 224
Milligan, G. W.      79 84 138 139 140 141 153 175 177 179 185 188
Minimum mean-square-error projection      31
Minimum method      65
Minimum spanning tree and DeLaunay triangulation      125
Minimum spanning tree and Gestalt principle      121
Minimum spanning tree and single-link clustering      70
Minimum spanning tree and triangulation      41
Minimum spanning tree and unfolding data      45
Minimum spanning tree, definition      271
Minimum spanning tree, in clustering tendency      214
Minimum variance method      80
Minimum variance partition      93
Minkowski metric      14 15 47
Missing data      19
Mitchell, O. R.      228
Mitiche, A.      228
Mixture decomposition      117
Mixture density      117
Mizoguchi, R.      53 123
Mode separation      120
Mode-seeking      117-18
Mojena, R.      139
Moment of inertia      25
Monothetic clustering algorithm      58
Monotone methods and ultrametricity      83
Monotone regression      50
Monotonicity and crossovers in dendrogram      83
Monotonicity and matrix updating      79
Monotonicity and ultrametricity      70
Monotonicity and updating formula      84
Monotonicity with SAHN methods      80
Monotonicity, in SAHN algorithms      84
Monte Cario Analysis in hypothesis testing      145
Monte Cario Analysis in hypothesis testing with test of cluster validity      161
Monte Cario Analysis in hypothesis testing, in test for nonrandom structure      162
Monte Cario Analysis in hypothesis testing, in tests for randomness      215 218
Monte Carlo analysis      155-59
Monte Carlo analysis of baseline distribution for square-error      178
Monte Carlo analysis of CPCC      166
Monte Carlo analysis with Hubert’s $\Gamma$ statistic      150 153
Monte Carlo analysis, in clustering methodology      137
Monte Carlo estimate, crude      155 157
Monte Carlo sampling      155-56 158
Monte Carlo studies of external indices of partitional adequacy      176
Monte Carlo studies of stress distribution      51
Monte Carlo studies with DB statistic      186
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