Cantitate/Preț
Produs
Total produse
Vezi coșul
Clusters, Orders, and Trees: Methods and Applications de Fuad Aleskerov

Clusters, Orders, and Trees: Methods and Applications

Editat de Fuad Aleskerov, Boris Goldengorin, Panos M Pardalos
en Limba Engleză Paperback – 23 aug 2016
The volume is dedicated to Boris Mirkin on the occasion of his 70th birthday. In addition to his startling PhD results in abstract automata theory, Mirkin’s ground breaking contributions in various fields of decision making and data analysis have marked the fourth quarter of the 20th century and beyond. Mirkin has done pioneering work in group choice, clustering, data mining and knowledge discovery aimed at finding and describing non-trivial or hidden structures—first of all, clusters, orderings and hierarchies—in multivariate and/or network data.
This volume contains a collection of papers reflecting recent developments rooted in Mirkin’s fundamental contribution to the state-of-the-art in group choice, ordering, clustering, data mining and knowledge discovery. Researchers, students and software engineers will benefit from new knowledge discovery techniques and application directions.
Citește tot Restrânge

Preț: 62149 lei

Preț vechi: 73117 lei
-15%

Puncte Express: 932
Preț estimativ în valută:
10993€ • 13035$ • 9577£

Carte tipărită la comandă

Livrare economică 25 martie-08 aprilie

 Adaugă în coș

Wish list
Gift list
Am citit!
Adaugă în listă

Specificații

ISBN-13: 9781493947997
ISBN-10: 1493947990
Pagini: 404
Ilustrații: XI, 404 p. 80 illus., 28 illus. in color.
Dimensiuni: 155 x 235 x 23 mm
Greutate: 0.63 kg
Ediția:Softcover Reprint of the Original 1st 2014 edition
Editura: Springer
Locul publicării:New York, NY, United States

Cuprins

Three and One Questions to Dr. B. Mirkin about Complexity Statistics (I. Mandel).- Section 1.- A Polynomial Algorithm for a Class of 0-1 Fractional Programming Problems Involving Composite Functions, with an Application to Additive Clustering (P. Hansen, C. Meyer).- Experiments with a Non-Convex Variance-Based Clustering Criterion (R.F. Toso, E.V. Bauman, C.A. Kulikowski, I.B. Muchnik).- Strategy-Proof Location Functions on Finite Graphs (F.R. McMorris, H.M. Mulder, F.S. Roberts).- A Pseudo-Boolean Approach to the Market Graph Analysis by Means of the p-Median Model (B. Goldengorin, A. Kocheturov, P.M. Pardalos).- Clustering as an Approach to 3D Reconstruction Problems (S. Archangelski, I. Muchnik).- Selecting the Minkowski Exponent for Intelligent K-Means with Feature Weighting (R. Cordeiro de Amorim, B. Mirkin).- High Dimensional Data Classification (V. Pappu, P.M. Pardalos).- Algorithm FRiS-TDR for Generalized Classification of the Labeled, Semi-Labeled and Unlabeled Datasets (I.A. Borisova, N.G. Zagoruiko).- From Separating to Proximal Plane Classifiers: A Review (M.B. Ferraro, M.R. Guarracino).- A Note on the Effectiveness of the Least Squares Consensus Clustering (B. Mirkin, A. Shestakov).- Section 2.- Single or Multiple Consensus for Linear Orders (A. Guenoche).- Choice Functions on Tree Quasi-Orders (R.C. Powers, F. McMorris).- Weak Hierarchies: a Central Clustering Structure (P. Bertrand, J. Diatta).- Some Observations on Oligarchies, Internal Direct Sums and Lattice Congruences (M.F. Janowitz).- Thinking Ultrametrically, Thinking p-Adically (F. Murtagh).- A New Algorithm for Inferring Hybridization Events Based on the Detection of Horizontal Gene Transfers (V. Makarenkov, A. Box, P. Legendre).- Section 3.- Meaningless Statements in Landscape Ecology and Sustainable Environments (F. Roberts).- Nearest Neighbour in Least Squares Data Imputation Algorithms for Marketing Data (I. Wasito). An AST Method for Scoring String-to-Text Similarity in Semantic Text Analysis (K. Chernyak, B. Mirkin).- Improving Web Search Relevance with Learning Structure of Domain Concepts (B. Galitsky, B. Kovalerchuk).- Linear Regression via Elastic Net: Non-Enumerative Leave-One-Out Verification of Feature Selection (E. Chernousova, N. Razin, O. Krasotkina, V. Mottl, D. Windridge).- The Manipulability Index in the IANC Model (Y. Veselova).

Textul de pe ultima copertă

The volume is dedicated to Boris Mirkin on the occasion of his 70th birthday. In addition to his startling PhD results in abstract automata theory, Mirkin’s ground breaking contributions in various fields of decision making and data analysis have marked the fourth quarter of the 20th century and beyond. Mirkin has done pioneering work in group choice, clustering, data mining and knowledge discovery aimed at finding and describing non-trivial or hidden structures—first of all, clusters, orderings, and hierarchies—in multivariate and/or network data.

This volume contains a collection of papers reflecting recent developments rooted in Mirkin's fundamental contribution to the state-of-the-art in group choice, ordering, clustering, data mining, and knowledge discovery. Researchers, students, and software engineers will benefit from new knowledge discovery techniques and application directions.

Caracteristici

Contains new models and algorithms for knowledge discoveries Features new tools for developing practical algorithms for solving problems in data analysis Opens a new direction in addressing difficult questions in data analysis for either well-known tools (like K-means) or recently developed advanced tools Includes supplementary material: sn.pub/extras