An Introduction To Cluster Science
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| Author | : Phuong Mai Dinh |
| Publisher | : John Wiley & Sons |
| Total Pages | : 258 |
| Release | : 2013-09-30 |
| Genre | : Science |
| ISBN | : 3527675701 |
Filling the need for a solid textbook, this short primer in cluster science is ideal for a one-semester lecture for advanced undergraduate students. It is based on a series of lectures given by the well-established and recognized authors for the past ten years. The book covers both the basics of the domain as well as up-to-date developments. It can be divided roughly into two parts. The first three chapters introduce basic concepts of cluster science. Chapter 1 provides a general introduction, complemented by chapter 2 on experimental and chapter 3 on theoretical aspects. The second half of the book is devoted to a systematic presentation of free cluster properties, and to a thorough discussion of the impact of clusters in other domains of science. These explicitly worked-out links between cluster physics and other research areas are unique both in terms of fundamental aspects and of applications, and cannot be found elsewhere in the literature. Also suitable for researchers outside of the field looking for an introduction to cluster science.
| Author | : Leonard Kaufman |
| Publisher | : Wiley-Interscience |
| Total Pages | : 376 |
| Release | : 1990-03-22 |
| Genre | : Mathematics |
| ISBN | : |
Partitioning around medoids (Program PAM). Clustering large applications (Program CLARA). Fuzzy analysis (Program FANNY). Agglomerative Nesting (Program AGNES). Divisive analysis (Program DIANA). Monothetic analysis (Program MONA). Appendix.
| Author | : Paolo Giordani |
| Publisher | : Springer Nature |
| Total Pages | : 340 |
| Release | : 2020-08-27 |
| Genre | : Mathematics |
| ISBN | : 9811305536 |
The purpose of this book is to thoroughly prepare the reader for applied research in clustering. Cluster analysis comprises a class of statistical techniques for classifying multivariate data into groups or clusters based on their similar features. Clustering is nowadays widely used in several domains of research, such as social sciences, psychology, and marketing, highlighting its multidisciplinary nature. This book provides an accessible and comprehensive introduction to clustering and offers practical guidelines for applying clustering tools by carefully chosen real-life datasets and extensive data analyses. The procedures addressed in this book include traditional hard clustering methods and up-to-date developments in soft clustering. Attention is paid to practical examples and applications through the open source statistical software R. Commented R code and output for conducting, step by step, complete cluster analyses are available. The book is intended for researchers interested in applying clustering methods. Basic notions on theoretical issues and on R are provided so that professionals as well as novices with little or no background in the subject will benefit from the book.
| Author | : Ronald S. King |
| Publisher | : Mercury Learning and Information |
| Total Pages | : 363 |
| Release | : 2015-05-12 |
| Genre | : Computers |
| ISBN | : 1942270135 |
Cluster analysis is used in data mining and is a common technique for statistical data analysis used in many fields of study, such as the medical & life sciences, behavioral & social sciences, engineering, and in computer science. Designed for training industry professionals or for a course on clustering and classification, it can also be used as a companion text for applied statistics. No previous experience in clustering or data mining is assumed. Informal algorithms for clustering data and interpreting results are emphasized. In order to evaluate the results of clustering and to explore data, graphical methods and data structures are used for representing data. Throughout the text, examples and references are provided, in order to enable the material to be comprehensible for a diverse audience. A companion disc includes numerous appendices with programs, data, charts, solutions, etc. eBook Customers: Companion files are available for downloading with order number/proof of purchase by writing to the publisher at [email protected]. FEATURES *Places emphasis on illustrating the underlying logic in making decisions during the cluster analysis *Discusses the related applications of statistic, e.g., Ward’s method (ANOVA), JAN (regression analysis & correlational analysis), cluster validation (hypothesis testing, goodness-of-fit, Monte Carlo simulation, etc.) *Contains separate chapters on JAN and the clustering of categorical data *Includes a companion disc with solutions to exercises, programs, data sets, charts, etc.
| Author | : Cram101 Textbook Reviews |
| Publisher | : Cram101 |
| Total Pages | : 90 |
| Release | : 2014-05-07 |
| Genre | : |
| ISBN | : 9781497006669 |
Never HIGHLIGHT a Book Again! Includes all testable terms, concepts, persons, places, and events. Cram101 Just the FACTS101 studyguides gives all of the outlines, highlights, and quizzes for your textbook with optional online comprehensive practice tests. Only Cram101 is Textbook Specific. Accompanies: 9783527411184. This item is printed on demand.
| Author | : Günter Schmid |
| Publisher | : John Wiley & Sons |
| Total Pages | : 570 |
| Release | : 2008-07-11 |
| Genre | : Science |
| ISBN | : 3527616063 |
This book offers a comprehensive overview of the rapidly developing field of cluster science. In an interdisciplinary approach, basic concepts as well as recent developments in research and practical applications are authoritatively discussed by leading authors. Topics covered include 'naked' metal clusters, clusters stabilized by ligands, clusters in solids, and colloids. The reader will find answers to questions like: * How many metal atoms must a particle have to exhibit metallic properties? * How can the large specific surface of clusters and colloids be employed in catalysts? * How can metal clusters be introduced into solid hosts? * Which effects are responsible for the transition from isolated to condensed clusters? The editor has succeeded in bringing the contributions of various authors together into a homogeneous, readable book, which will be useful for the academic and industrial reader alike.
| Author | : Leonard Kaufman |
| Publisher | : John Wiley & Sons |
| Total Pages | : 368 |
| Release | : 2009-09-25 |
| Genre | : Mathematics |
| ISBN | : 0470317485 |
The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "Cluster analysis is the increasingly important and practical subject of finding groupings in data. The authors set out to write a book for the user who does not necessarily have an extensive background in mathematics. They succeed very well." —Mathematical Reviews "Finding Groups in Data [is] a clear, readable, and interesting presentation of a small number of clustering methods. In addition, the book introduced some interesting innovations of applied value to clustering literature." —Journal of Classification "This is a very good, easy-to-read, and practical book. It has many nice features and is highly recommended for students and practitioners in various fields of study." —Technometrics An introduction to the practical application of cluster analysis, this text presents a selection of methods that together can deal with most applications. These methods are chosen for their robustness, consistency, and general applicability. This book discusses various types of data, including interval-scaled and binary variables as well as similarity data, and explains how these can be transformed prior to clustering.
| Author | : Hellmut Haberland |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 435 |
| Release | : 2013-11-11 |
| Genre | : Science |
| ISBN | : 3642843298 |
Clusters of Atoms and Molecules I is devoted to theoretical concepts and experimental techniques important in the rapidly expanding field of cluster science. Cluster properties are dicussed for clusters composed of alkali metals, semiconductors, transition metals, carbon, oxides and halides of alkali metals, rare gases, and neutral molecules. The book contains several well-integrated treatments, all prepared by experts. Each contribution starts out as simple as possible and ends with the latest results, so that the book can serve as a text for a course, an introduction into the field, or as a reference book for the expert.
| Author | : Paul-Gerhard Reinhard |
| Publisher | : John Wiley & Sons |
| Total Pages | : 341 |
| Release | : 2008-07-11 |
| Genre | : Science |
| ISBN | : 3527621016 |
Clusters as mesoscopic particles represent an intermediate state of matter between single atoms and solid material. The tendency to miniaturise technical objects requires knowledge about systems which contain a "small" number of atoms or molecules only. This is all the more true for dynamical aspects, particularly in relation to the qick development of laser technology and femtosecond spectroscopy. Here, for the first time is a highly qualitative introduction to cluster physics. With its emphasis on cluster dynamics, this will be vital to everyone involved in this interdisciplinary subject. The authors cover the dynamics of clusters on a broad level, including recent developments of femtosecond laser spectroscopy on the one hand and time-dependent density functional theory calculations on the other.
| Author | : Rui Xu |
| Publisher | : John Wiley & Sons |
| Total Pages | : 400 |
| Release | : 2008-11-03 |
| Genre | : Mathematics |
| ISBN | : 0470382783 |
This is the first book to take a truly comprehensive look at clustering. It begins with an introduction to cluster analysis and goes on to explore: proximity measures; hierarchical clustering; partition clustering; neural network-based clustering; kernel-based clustering; sequential data clustering; large-scale data clustering; data visualization and high-dimensional data clustering; and cluster validation. The authors assume no previous background in clustering and their generous inclusion of examples and references help make the subject matter comprehensible for readers of varying levels and backgrounds.
