Mathematical Classification and Clustering

1. Classes and Clusters. 2. Geometry of Data. 3. Clustering Algorithms: A Review. 4. Single Cluster Clustering. 5. Partition: Square Data Table. 6. Partition: Rectangular Table. 7. Hierarchy as a Clustering Structure.

[1]  H. P. Friedman,et al.  On Some Invariant Criteria for Grouping Data , 1967 .

[2]  Varghese S. Jacob,et al.  A study of the classification capabilities of neural networks using unsupervised learning: A comparison withK-means clustering , 1994 .

[3]  Gilbert Saporta,et al.  About maximal association criteria in linear analysis and in cluster analysis , 1987 .

[4]  Leo A. Goodman,et al.  Criteria for Determining Whether Certain Categories in a Cross-Classification Table Should Be Combined, with Special Reference to Occupational Categories in an Occupational Mobility Table , 1981, American Journal of Sociology.

[5]  Simon Kasif,et al.  A System for Induction of Oblique Decision Trees , 1994, J. Artif. Intell. Res..

[6]  George W. Furnas,et al.  The estimation of ultrametric and path length trees from rectangular proximity data , 1984 .

[7]  A. Dress,et al.  Weak hierarchies associated with similarity measures--an additive clustering technique. , 1989, Bulletin of mathematical biology.

[8]  B. Everitt,et al.  Applied Multivariate Data Analysis. , 1993 .

[9]  Ye.A Smolenskii.  A method for the linear recording of graphs , 1963 .

[10]  Temple F. Smith,et al.  On the similarity of dendrograms. , 1978, Journal of theoretical biology.

[11]  Fred S. Roberts,et al.  INDIFFERENCE AND SERIATION , 1979 .

[12]  Wen-Hsiung Li,et al.  Fundamentals of molecular evolution , 1990 .

[13]  J. Hartigan.  REPRESENTATION OF SIMILARITY MATRICES BY TREES , 1967 .

[14]  William K. Estes,et al.  Classification and cognition , 1994 .

[15]  Boris G. Mirkin,et al.  Approximation of Association Data by Structures and Clusters , 1993, Quadratic Assignment and Related Problems.

[16]  Iven Van Mechelen,et al.  A HIERARCHICAL CLASSES MODEL: THEORY AND METHOD WITH APPLICATIONS IN PSYCHOLOGY AND PSYCHOPATHOLOGY , 1996 .

[17]  J. Carroll,et al.  Spatial, non-spatial and hybrid models for scaling , 1976 .

[18]  Jue Xue,et al.  Edge-maximal triangulated subgraphs and heuristics for the maximum clique problem , 1994, Networks.

[19]  A. Dress,et al.  A canonical decomposition theory for metrics on a finite set , 1992 .

[20]  Beat Kleiner,et al.  10 Graphical techniques for multivariate data and for clustering , 1982, Classification, Pattern Recognition and Reduction of Dimensionality.

[21]  Fionn Murtagh,et al.  NEURAL NETWORKS FOR CLUSTERING , 1996 .

[22]  Teuvo Kohonen,et al.  Self-organization and associative memory: 3rd edition , 1989 .

[23]  M. Steel,et al.  Distributions of Tree Comparison Metrics—Some New Results , 1993 .

[24]  Charles V. Packer,et al.  Applying row-column permutation to matrix representations of large citation networks , 1989, Inf. Process. Manag..

[25]  M. F. Janowitz,et al.  An Order Theoretic Model for Cluster Analysis , 1978 .

[26]  Martin Schader,et al.  Pyramidal classification based on incomplete dissimilarity data , 1994 .

[27]  R. F. Ling.  A Probability Theory of Cluster Analysis , 1973 .

[28]  B. Leclerc,et al.  La comparaison des hiérarchies: indices et métriques , 1985 .

[29]  L. Hubert,et al.  Combinatorial Data Analysis , 1992 .

[30]  John C. Gower,et al.  Measures of Similarity, Dissimilarity and Distance , 1985 .

[31]  Bernard Van Cutsem,et al.  Classification And Dissimilarity Analysis , 1994 .

[32]  F. Marcotorchino,et al.  Block seriation problems: A unified approach. Reply to the problem of H. Garcia and J. M. Proth (Applied Stochastic Models and Data Analysis, 1, (1), 25–34 (1985)) , 1987 .

[33]  Henry D. Shapiro,et al.  An Exact Characterization of Greedy Structures , 1993, IPCO.

[34]  L. A. Goodman,et al.  Measures of association for cross classifications , 1979 .

[35]  I. B. Muchnik,et al.  Incomplete classifications of a finite set of objects using Monotone Systems , 1989 .

[36]  Roger N. Shepard,et al.  Additive clustering: Representation of similarities as combinations of discrete overlapping properties. , 1979 .

[37]  G. Estabrook,et al.  An idealized concept of the true cladistic character , 1975 .

[38]  Kellogg S. Booth,et al.  Testing for the Consecutive Ones Property, Interval Graphs, and Graph Planarity Using PQ-Tree Algorithms , 1976, J. Comput. Syst. Sci..

[39]  G. Celeux,et al.  A Classification EM algorithm for clustering and two stochastic versions , 1992 .

[40]  A. Tversky,et al.  Extended similarity trees , 1986 .

[41]  Babu O. Narayanan,et al.  On the approximability of numerical taxonomy , 1996 .

[42]  Derek Wilton Langridge.  Classification: Its Kinds, Elements, Systems and Applications , 1992 .

[43]  Rudolf Wille,et al.  On the Classification of Monotone-Equivariant Cluster Methods , 1993, Partitioning Data Sets.

[44]  W. T. Williams,et al.  Multivariate Methods in Plant Ecology: I. Association-Analysis in Plant Communities , 1959 .

[45]  John Allen Paulos,et al.  Mathematics and Humor , 1980 .

[46]  D. Robinson.  Comparison of labeled trees with valency three , 1971 .

[47]  E. Diday,et al.  AN EXTENSION OF HIERARCHICAL CLUSTERING : THE PYRAMIDAL PRESENTATION , 1986 .

[48]  Shizuhiko Nishisato,et al.  Elements of Dual Scaling: An Introduction To Practical Data Analysis , 1993 .

[49]  W. S. Robinson.  A Method for Chronologically Ordering Archaeological Deposits , 1951, American Antiquity.

[50]  J. Bezdek.  Numerical taxonomy with fuzzy sets , 1974 .

[51]  Gary D. Sandefur,et al.  Opportunity and Change. , 1978 .

[52]  Manuel Zacklad,et al.  Systematic building of conceptual classification systems with C-KAT , 1993, Int. J. Hum. Comput. Stud..

[53]  K. Florek,et al.  Sur la liaison et la division des points d'un ensemble fini , 1951 .

[54]  F. B. Baulieu.  A classification of presence/absence based dissimilarity coefficients , 1989 .

[55]  I. B. Muchnik,et al.  of Classification 10 : 219-240 ( 1993 ) Fixed Points Approach to Clustering * , 1993 .

[56]  Pierre Hansen,et al.  Bicriterion Cluster Analysis , 1980, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[57]  P. H. A. Sneath,et al.  Thirty Years of Numerical Taxonomy , 1995 .

[58]  Thomas H. Carr,et al.  Psychology: The Study of Human Experience. , 1986 .

[59]  Arnold G. Kluge,et al.  A Numerical Approach to Phylogenetic Systematics , 1970 .

[60]  John A. Hartigan,et al.  Clustering Algorithms , 1975 .

[61]  Jean Diatta,et al.  From Apresjan Hierarchies and Bandelt-Dress Weak hierarchies to Quasi-hierarchies , 1994 .

[62]  F. Bass,et al.  An experimental study of relationships between attitudes, brand preference, and choice , 1972 .

[63]  Earl E. Swartzlander,et al.  Introduction to Mathematical Techniques in Pattern Recognition , 1973 .

[64]  A. Raftery,et al.  Model-based Gaussian and non-Gaussian clustering , 1993 .

[65]  John H. Gennari,et al.  Focused Concept Formation , 1989, ML.

[66]  P. Arabie,et al.  Three-Way Scaling and Clustering. , 1991 .

[67]  J. Gower.  A comparison of some methods of cluster analysis. , 1967, Biometrics.

[68]  Uppaluri S. R. Murty,et al.  Graph Theory with Applications , 1978 .

[69]  R. Shepard.  Metric structures in ordinal data , 1966 .

[70]  Panos M. Pardalos,et al.  The Quadratic Assignment Problem: A Survey and Recent Developments , 1993, Quadratic Assignment and Related Problems.

[71]  B. G. Mirkin,et al.  15 – On the Problem of Reconciling Partitions* , 1975 .

[72]  G. N. Lance,et al.  A General Theory of Classificatory Sorting Strategies: 1. Hierarchical Systems , 1967, Comput. J..

[73]  Phipps Arabie,et al.  Constructing blockmodels: How and why , 1978 .

[74]  J. Barthelemy,et al.  On the use of ordered sets in problems of comparison and consensus of classifications , 1986 .

[75]  Richard O. Duda,et al.  Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.

[76]  B. Mirkin.  A sequential fitting procedure for linear data analysis models , 1990 .

[77]  R. Fisher.  THE USE OF MULTIPLE MEASUREMENTS IN TAXONOMIC PROBLEMS , 1936 .

[78]  Z. Hubálek.  COEFFICIENTS OF ASSOCIATION AND SIMILARITY, BASED ON BINARY (PRESENCE‐ABSENCE) DATA: AN EVALUATION , 1982 .

[79]  P. Boeck,et al.  Hierarchical classes: Model and data analysis , 1988 .

[80]  J. H. Ward.  Hierarchical Grouping to Optimize an Objective Function , 1963 .

[81]  Gérard Govaert.  La classification croisée , 1989, Monde des Util. Anal. Données.

[82]  R. Dykstra.  An Algorithm for Restricted Least Squares Regression , 1983 .

[83]  A. Agresti,et al.  Analysis of Ordinal Categorical Data. , 1985 .

[84]  Kenneth Steiglitz,et al.  Combinatorial Optimization: Algorithms and Complexity , 1981 .

[85]  Eduardo D. Sontag.  Sigmoids Distinguish More Efficiently Than Heavisides , 1989, Neural Computation.

[86]  Irène Charon,et al.  The noising method: a new method for combinatorial optimization , 1993, Oper. Res. Lett..

[87]  Edwin Diday,et al.  Orders and overlapping clusters by pyramids , 1987 .

[88]  J. V. Ness,et al.  Space-conserving agglomerative algorithms , 1996 .

[89]  M. O. Hill,et al.  TWINSPAN: a FORTRAN program of arranging multivariate data in an ordered two way table by classification of individual and attributes , 1979 .

[90]  Bernard Monjardet,et al.  Metrics on partially ordered sets - A survey , 1981, Discret. Math..

[91]  Robert E. Tarjan,et al.  A Fast Parametric Maximum Flow Algorithm and Applications , 1989, SIAM J. Comput..

[92]  N. Saitou,et al.  The neighbor-joining method: a new method for reconstructing phylogenetic trees. , 1987, Molecular biology and evolution.

[93]  P. Buneman.  The Recovery of Trees from Measures of Dissimilarity , 1971 .

[94]  Hans-Jürgen Bandelt.  Recognition of Tree Metrics , 1990, SIAM J. Discret. Math..

[95]  B. S. Duran,et al.  Cluster Analysis: A Survey , 1974 .

[96]  大沢 省三,et al.  Evolution of life : fossils, molecules, and culture , 1991 .

[97]  Robert H. Somers,et al.  A new asymmetric measure of association for ordinal variables. , 1962 .

[98]  M R Segal,et al.  Extending the elements of tree-structured regression , 1995, Statistical methods in medical research.

[99]  A. Kovalenko,et al.  A kn-Nearest Neighbour Algorithm for Unimodal Clusters , 1993 .

[100]  Peter G. Bryant,et al.  Large-sample results for optimization-based clustering methods , 1991 .

[101]  M. Greenacre.  Correspondence analysis in practice , 1993 .

[102]  A. Dress,et al.  Reconstructing the shape of a tree from observed dissimilarity data , 1986 .

[103]  J. A. Hartigan,et al.  Modal Blocks in Dentition of West Coast Mammals , 1976 .

[104]  Brian P. Dawkins.  Investigating the Geometry of a p-Dimensional Data Set , 1995 .

[105]  I. Jolliffe,et al.  Nonlinear Multivariate Analysis , 1992 .

[106]  M Damashek,et al.  Gauging Similarity with n-Grams: Language-Independent Categorization of Text , 1995, Science.

[107]  Alain Guénoche,et al.  Trees and proximity representations , 1991, Wiley-Interscience series in discrete mathematics and optimization.

[108]  P. Arabie,et al.  Mapclus: A mathematical programming approach to fitting the adclus model , 1980 .

[109]  René Baire,et al.  Lecons sur les fonctions discontinues , 1905 .

[110]  Hans-Hermann Bock,et al.  Probabilistic Aspects in Cluster Analysis , 1989 .

[111]  James C. Bezdek.  Integration and generalization of LVQ and c-means clustering (Invited Paper) , 1992, Other Conferences.

[112]  Lynette Hirschman,et al.  Evaluating Message Understanding Systems: An Analysis of the Third Message Understanding Conference (MUC-3) , 1993, CL.

[113]  W. Warde,et al.  A mathematical comparison of the members of an infinite family of agglomerative clustering algorithms , 1979 .

[114]  R. M. Hayes,et al.  Measurement theory, with applications to decision-making, utility, and the social sciences: Fred S. Roberts, Vol. 7 of the encyclopedia of mathematics and its applications. Addison-Wesley, advanced book program, Reading, Mass., 1979, pp. 420, $24.50 , 1980 .

[115]  William M. Rand,et al.  Objective Criteria for the Evaluation of Clustering Methods , 1971 .

[116]  B. Jaumard,et al.  Efficient algorithms for divisive hierarchical clustering with the diameter criterion , 1990 .

[117]  Bruno Leclerc,et al.  Minimum spanning trees for tree metrics: abridgements and adjustments , 1995 .

[118]  S.,et al.  An Efficient Heuristic Procedure for Partitioning Graphs , 2022 .

[119]  B. Mirkin,et al.  Monotone Linkage Clustering and Quasi-Convex Set Functions , 1995 .

[120]  Robert H. Berk.  Assignment Methods in Combinatorial Data Analysis , 1989 .

[121]  N. Nakamura,et al.  Space-distorting properties in agglomerative hierarchical clustering algorithms and a simplified method for combinatorial method , 1989 .

[122]  D. N. Geary.  Mixture Models: Inference and Applications to Clustering , 1989 .

[123]  C. Edelbrock.  Mixture Model Tests Of Hierarchical Clustering Algorithms: The Problem Of Classifying Everybody. , 1979, Multivariate behavioral research.

[124]  Geoffrey E. Hinton,et al.  Learning internal representations by error propagation , 1986 .

[125]  Teuvo Kohonen,et al.  Self-Organizing Maps , 2010 .

[126]  G H Ball,et al.  A clustering technique for summarizing multivariate data. , 1967, Behavioral science.

[127]  W. C. Berwick Sayers.  An introduction to library classification , 1922 .

[128]  William F. Hyde.  Improving productivity by classification, coding and data base standardization , 1981 .

[129]  C. Mallows,et al.  A Method for Comparing Two Hierarchical Clusterings , 1983 .

[130]  Michael Greenacre,et al.  Clustering the rows and columns of a contingency table , 1988 .

[131]  Pierre Hansen,et al.  Maximum Split Single Cluster Clustering , 1993 .

[132]  N. Mantel.  The detection of disease clustering and a generalized regression approach. , 1967, Cancer research.

[133]  P. Arabie,et al.  Indclus: An individual differences generalization of the adclus model and the mapclus algorithm , 1983 .

[134]  R. Tryon.  Cluster Analysis , 1939 .

[135]  E. Diday,et al.  Learning hierarchical clustering from examples , 1984 .

[136]  Fred R. McMorris,et al.  COMPARISON OF UNDIRECTED PHYLOGENETIC TREES BASED ON SUBTREES OF FOUR EVOLUTIONARY UNITS , 1985 .

[137]  O. Gascuel.  A note on Sattath and Tversky's, Saitou and Nei's, and Studier and Keppler's algorithms for inferring phylogenies from evolutionary distances. , 1994, Molecular biology and evolution.

[138]  Mark A. Gluck,et al.  Information, Uncertainty and the Utility of Categories , 1985 .

[139]  G. Lenski,et al.  SOCIETAL TAXONOMIES: Mapping the Social Universe , 1994 .

[140]  Jan de Leeuw,et al.  Block-relaxation Algorithms in Statistics , 1994 .

[141]  George L. Nemhauser,et al.  Easy and hard bottleneck location problems , 1979, Discret. Appl. Math..

[142]  D. Penny,et al.  The Use of Tree Comparison Metrics , 1985 .

[143]  M. Jambu.  Classification automatique pour l'analyse des données , 1978 .

[144]  Qiwen Zhang,et al.  A new clustering algorithm with multiple runs of iterative procedures , 1991, Pattern Recognit..

[145]  Eduardo Bayro-Corrochano,et al.  Self-organizing neural-network-based pattern clustering method with fuzzy outputs , 1994, Pattern Recognit..

[146]  S. Boorman,et al.  Metrics on spaces of finite trees , 1973 .

[147]  James C. Bezdek,et al.  Pattern Recognition with Fuzzy Objective Function Algorithms , 1981, Advanced Applications in Pattern Recognition.

[148]  J. Gower,et al.  Minimum Spanning Trees and Single Linkage Cluster Analysis , 1969 .

[149]  Pierre Hansen,et al.  Average-Linkage Divisive Hierarchical Clustering , 1991 .

[150]  B. Leclerc.  Description combinatoire des ultramétriques , 1981 .

[151]  N. X. Luong,et al.  Représentations arborées de mesures de dissimilarité , 1986 .

[152]  L. Hubert,et al.  Additive two-mode clustering: The error-variance approach revisited , 1995 .

[153]  G. Keren,et al.  Recognition models of alphanumeric characters. , 1981, Perception & psychophysics.

[154]  P. Arabie,et al.  Marketing applications of sequencing and partitioning of nonsymmetric and/or two-mode matrices , 1988 .

[155]  L. Cavalli-Sforza,et al.  PHYLOGENETIC ANALYSIS: MODELS AND ESTIMATION PROCEDURES , 1967, Evolution; international journal of organic evolution.

[156]  C. J. Jardine,et al.  The structure and construction of taxonomic hierarchies , 1967 .

[157]  F. Rohlf.  Adaptive Hierarchical Clustering Schemes , 1970 .

[158]  Erhard Godehardt,et al.  Graphs as Structural Models , 1988 .

[159]  H. Ralambondrainy,et al.  A conceptual version of the K-means algorithm , 1995, Pattern Recognit. Lett..

[160]  J. Carroll,et al.  An alternating combinatorial optimization approach to fitting the INDCLUS and generalized INDCLUS models , 1994 .

[161]  John W. Van Ness,et al.  Metric admissibility and agglomerative clustering , 1994 .

[162]  Harry Hall Sisler.  Electronic structure, properties, and the periodic law , 1963 .

[163]  Jerome D. Greene.  Commentary on “A Brand Switching Model with Implications for Marketing Strategies” , 1989 .

[164]  F. Gebhardt.  Discovering interesting statements from a database , 1994 .

[165]  G. Celeux,et al.  Clustering criteria for discrete data and latent class models , 1991 .

[166]  H. E. Daniels,et al.  The Relation Between Measures of Correlation in the Universe of Sample Permutations , 1944 .

[167]  G. Milligan.  Ultrametric hierarchical clustering algorithms , 1979 .

[168]  Forrest W. Young,et al.  Multivariate Statistical Visualization , 1992 .

[169]  J. Hartigan.  Direct Clustering of a Data Matrix , 1972 .

[170]  Emile H. L. Aarts,et al.  Simulated Annealing: Theory and Applications , 1987, Mathematics and Its Applications.

[171]  Boris Mirkin,et al.  CLUSTERING AND MULTIDIMENSIONAL SCALING IN RUSSIA (1960–1990): A REVIEW , 1996 .

[172]  R. Michalski,et al.  Learning from Observation: Conceptual Clustering , 1983 .

[173]  B. G. Mirkin,et al.  Correspondence analysis and classification , 1993 .

[174]  Harry Shum,et al.  Principal Component Analysis with Missing Data and Its Application to Polyhedral Object Modeling , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[175]  Rudolf Wille.  Knowledge acquisition by methods of formal concept analysis , 1989 .

[176]  Sean McGuinness,et al.  The greedy clique decomposition of a graph , 1994, J. Graph Theory.

[177]  P. Orlik,et al.  An error variance approach to two-mode hierarchical clustering , 1993 .

[178]  stanley W. Jevons,et al.  The principles of science , 1960 .

[179]  Pierre Hansen,et al.  A Comparison of Algorithms for the Maximum Clique Problem , 1992 .

[180]  E. N. Adams,et al.  N-trees as nestings: Complexity, similarity, and consensus , 1986 .

[181]  Anil K. Jain,et al.  Algorithms for Clustering Data , 1988 .

[182]  R. Sokal,et al.  Optimisation en Classification Automatique. , 1984 .

[183]  J. A. Studier,et al.  A note on the neighbor-joining algorithm of Saitou and Nei. , 1988, Molecular biology and evolution.

[184]  W. A. Beyer,et al.  Additive evolutionary trees. , 1977, Journal of theoretical biology.

[185]  Claude Flament,et al.  L'analyse booléenne de questionnaires , 1976 .

[186]  H. J. RYSER,et al.  Intersection Properties of Finite Sets , 1973, J. Comb. Theory, Ser. A.

[187]  Ilya B. Muchnik,et al.  A Biologically Consistent Model for Comparing Molecular Phylogenies , 1995, J. Comput. Biol..

[188]  D. R. Fulkerson,et al.  Incidence matrices and interval graphs , 1965 .

[189]  A Dress,et al.  Split decomposition: a technique to analyze viral evolution. , 1993, Proceedings of the National Academy of Sciences of the United States of America.

[190]  P. Kloeden,et al.  Metric spaces of fuzzy sets , 1990 .

[191]  H. Colonius,et al.  Tree structures for proximity data , 1981 .

[192]  Ronald L. Breiger,et al.  The Social Class Structure of Occupational Mobility , 1981, American Journal of Sociology.

[193]  W. H. Day.  Computational complexity of inferring phylogenies from dissimilarity matrices. , 1987, Bulletin of mathematical biology.

[194]  Pierre Hansen,et al.  How to Choose K Entities Among N , 1994, Partitioning Data Sets.

[195]  C. V. Jawahar,et al.  Detection of clusters of distinct geometry: A step towards generalised fuzzy clustering , 1995, Pattern Recognit. Lett..

[196]  Stephen Grossberg,et al.  Self-Organizing Neural Networks for Supervised and Unsupervised Learning and Prediction , 1994 .

[197]  L. Devroye,et al.  The Strong Uniform Consistency of Nearest Neighbor Density Estimates. , 1977 .

[198]  R. Sokal,et al.  THE COMPARISON OF DENDROGRAMS BY OBJECTIVE METHODS , 1962 .

[199]  Alan F. Dutka,et al.  Fundamentals of data normalization , 1989 .

[200]  W. DeSarbo.  Gennclus: New models for general nonhierarchical clustering analysis , 1982 .

[201]  G. W. Milligan,et al.  A Study of the Comparability of External Criteria for Hierarchical Cluster Analysis. , 1986, Multivariate behavioral research.

[202]  K. Appel,et al.  The Solution of the Four-Color-Map Problem , 1977 .

[203]  Ronald L. Graham,et al.  On the History of the Minimum Spanning Tree Problem , 1985, Annals of the History of Computing.

[204]  G. W. Milligan,et al.  A study of standardization of variables in cluster analysis , 1988 .

[205]  Dan Gusfield,et al.  Efficient algorithms for inferring evolutionary trees , 1991, Networks.

[206]  J. MacQueen.  Some methods for classification and analysis of multivariate observations , 1967 .

[207]  John G. Hutchinson.  Organizations: Theory and Classical Concepts , 1967 .

[208]  Gregory Piatetsky-Shapiro,et al.  Knowledge Discovery in Databases: An Overview , 1992, AI Mag..

[209]  Linda M. Collins,et al.  BINCLUS: Nonhierarchical Clustering of Binary Data , 1986 .

[210]  George Cybenko,et al.  Approximation by superpositions of a sigmoidal function , 1989, Math. Control. Signals Syst..

[211]  Jorma Rissanen,et al.  Stochastic Complexity in Statistical Inquiry , 1989, World Scientific Series in Computer Science.

[212]  David W. Aha,et al.  A Comparative Evaluation of Sequential Feature Selection Algorithms , 1995, AISTATS.

[213]  J. Breckenridge.  Replicating Cluster Analysis: Method, Consistency, and Validity. , 1989, Multivariate behavioral research.

[214]  B. Mirkin.  Additive clustering and qualitative factor analysis methods for similarity matrices , 1987 .

[215]  L. Hubert,et al.  Quadratic assignment as a general data analysis strategy. , 1976 .

[216]  C.J.F. ter Braak.  Interpreting a hierarchical classification with simple discriminant functions: an ecological example , 1986 .

[217]  Steven J. Fenves,et al.  Applying AI clustering to engineering tasks , 1993, IEEE Expert.

[218]  Vijay V. Vazirani,et al.  Finding k-cuts within twice the optimal , 1991, [1991] Proceedings 32nd Annual Symposium of Foundations of Computer Science.

[219]  Ron Kohavi,et al.  Irrelevant Features and the Subset Selection Problem , 1994, ICML.

[220]  Mark S. Nixon,et al.  Generating-shrinking algorithm for learning arbitrary classification , 1994, Neural Networks.

[221]  J. Gower.  Some distance properties of latent root and vector methods used in multivariate analysis , 1966 .

[222]  F. Rohlf.  Methods of Comparing Classifications , 1974 .

[223]  Lawrence Hubert,et al.  The analysis of proximity matrices through sums of matrices having (anti‐)Robinson forms , 1994 .

[224]  M. Senechal,et al.  Crystalline Symmetries, An informal mathematical introduction , 1990 .

[225]  W. H. Day.  Optimal algorithms for comparing trees with labeled leaves , 1985 .

[226]  Brian Everitt,et al.  Cluster analysis , 1974 .

[227]  A. Tversky.  Features of Similarity , 1977 .

[228]  A. G. Arkad'ev,et al.  Computers and pattern recognition , 1967 .