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R and Data Mining

R and Data Mining PDF Author: Yanchang Zhao
Publisher: Academic Press
ISBN: 012397271X
Category : Mathematics
Languages : en
Pages : 256
Book Description
R and Data Mining introduces researchers, post-graduate students, and analysts to data mining using R, a free software environment for statistical computing and graphics. The book provides practical methods for using R in applications from academia to industry to extract knowledge from vast amounts of data. Readers will find this book a valuable guide to the use of R in tasks such as classification and prediction, clustering, outlier detection, association rules, sequence analysis, text mining, social network analysis, sentiment analysis, and more. Data mining techniques are growing in popularity in a broad range of areas, from banking to insurance, retail, telecom, medicine, research, and government. This book focuses on the modeling phase of the data mining process, also addressing data exploration and model evaluation. With three in-depth case studies, a quick reference guide, bibliography, and links to a wealth of online resources, R and Data Mining is a valuable, practical guide to a powerful method of analysis. Presents an introduction into using R for data mining applications, covering most popular data mining techniques Provides code examples and data so that readers can easily learn the techniques Features case studies in real-world applications to help readers apply the techniques in their work

R and Data Mining

R and Data Mining PDF Author: Yanchang Zhao
Publisher: Academic Press
ISBN: 012397271X
Category : Mathematics
Languages : en
Pages : 256
Book Description
R and Data Mining introduces researchers, post-graduate students, and analysts to data mining using R, a free software environment for statistical computing and graphics. The book provides practical methods for using R in applications from academia to industry to extract knowledge from vast amounts of data. Readers will find this book a valuable guide to the use of R in tasks such as classification and prediction, clustering, outlier detection, association rules, sequence analysis, text mining, social network analysis, sentiment analysis, and more. Data mining techniques are growing in popularity in a broad range of areas, from banking to insurance, retail, telecom, medicine, research, and government. This book focuses on the modeling phase of the data mining process, also addressing data exploration and model evaluation. With three in-depth case studies, a quick reference guide, bibliography, and links to a wealth of online resources, R and Data Mining is a valuable, practical guide to a powerful method of analysis. Presents an introduction into using R for data mining applications, covering most popular data mining techniques Provides code examples and data so that readers can easily learn the techniques Features case studies in real-world applications to help readers apply the techniques in their work

Data Mining with R

Data Mining with R PDF Author: Luis Torgo
Publisher: CRC Press
ISBN: 1315399091
Category : Business & Economics
Languages : en
Pages : 426
Book Description
Data Mining with R: Learning with Case Studies, Second Edition uses practical examples to illustrate the power of R and data mining. Providing an extensive update to the best-selling first edition, this new edition is divided into two parts. The first part will feature introductory material, including a new chapter that provides an introduction to data mining, to complement the already existing introduction to R. The second part includes case studies, and the new edition strongly revises the R code of the case studies making it more up-to-date with recent packages that have emerged in R. The book does not assume any prior knowledge about R. Readers who are new to R and data mining should be able to follow the case studies, and they are designed to be self-contained so the reader can start anywhere in the document. The book is accompanied by a set of freely available R source files that can be obtained at the book’s web site. These files include all the code used in the case studies, and they facilitate the "do-it-yourself" approach followed in the book. Designed for users of data analysis tools, as well as researchers and developers, the book should be useful for anyone interested in entering the "world" of R and data mining. About the Author Luís Torgo is an associate professor in the Department of Computer Science at the University of Porto in Portugal. He teaches Data Mining in R in the NYU Stern School of Business’ MS in Business Analytics program. An active researcher in machine learning and data mining for more than 20 years, Dr. Torgo is also a researcher in the Laboratory of Artificial Intelligence and Data Analysis (LIAAD) of INESC Porto LA.

Data Mining Applications with R

Data Mining Applications with R PDF Author: Yanchang Zhao
Publisher: Academic Press
ISBN: 0124115209
Category : Computers
Languages : en
Pages : 514
Book Description
Data Mining Applications with R is a great resource for researchers and professionals to understand the wide use of R, a free software environment for statistical computing and graphics, in solving different problems in industry. R is widely used in leveraging data mining techniques across many different industries, including government, finance, insurance, medicine, scientific research and more. This book presents 15 different real-world case studies illustrating various techniques in rapidly growing areas. It is an ideal companion for data mining researchers in academia and industry looking for ways to turn this versatile software into a powerful analytic tool. R code, Data and color figures for the book are provided at the RDataMining.com website. Helps data miners to learn to use R in their specific area of work and see how R can apply in different industries Presents various case studies in real-world applications, which will help readers to apply the techniques in their work Provides code examples and sample data for readers to easily learn the techniques by running the code by themselves

R Data Mining Blueprints

R Data Mining Blueprints PDF Author: Pradeepta Mishra
Publisher:
ISBN: 9781783989683
Category :
Languages : en
Pages : 260
Book Description


Data Mining

Data Mining PDF Author: Graham J. Williams
Publisher: Springer Science & Business Media
ISBN: 3540325476
Category : Computers
Languages : en
Pages : 341
Book Description
This volume provides a snapshot of the current state of the art in data mining, presenting it both in terms of technical developments and industrial applications. The collection of chapters is based on works presented at the Australasian Data Mining conferences and industrial forums. Authors include some of Australia's leading researchers and practitioners in data mining. The volume also contains chapters by regional and international authors.

Data Mining and Business Analytics with R

Data Mining and Business Analytics with R PDF Author: Johannes Ledolter
Publisher: John Wiley & Sons
ISBN: 1118572157
Category : Computers
Languages : en
Pages : 368
Book Description
Collecting, analyzing, and extracting valuable information froma large amount of data requires easily accessible, robust,computational and analytical tools. Data Mining and BusinessAnalytics with R utilizes the open source software R for theanalysis, exploration, and simplification of large high-dimensionaldata sets. As a result, readers are provided with the neededguidance to model and interpret complicated data and become adeptat building powerful models for prediction and classification. Highlighting both underlying concepts and practicalcomputational skills, Data Mining and Business Analytics withR begins with coverage of standard linear regression and theimportance of parsimony in statistical modeling. The book includesimportant topics such as penalty-based variable selection (LASSO);logistic regression; regression and classification trees;clustering; principal components and partial least squares; and theanalysis of text and network data. In addition, the bookpresents: • A thorough discussion and extensive demonstration of thetheory behind the most useful data mining tools • Illustrations of how to use the outlined concepts inreal-world situations • Readily available additional data sets and related Rcode allowing readers to apply their own analyses to the discussedmaterials • Numerous exercises to help readers with computing skillsand deepen their understanding of the material Data Mining and Business Analytics with R is an excellentgraduate-level textbook for courses on data mining and businessanalytics. The book is also a valuable reference for practitionerswho collect and analyze data in the fields of finance, operationsmanagement, marketing, and the information sciences.

Datamining und Computational Finance

Datamining und Computational Finance PDF Author: Georg Bol
Publisher: Springer-Verlag
ISBN: 3642576567
Category : Computers
Languages : de
Pages : 270
Book Description
Der Schwerpunkt des siebten Karlsruher Ökonometrie-Workshops lag auf der Anwendung Neuronaler Netze bei Finanzzeitreihen, dem Einsatz von Datamining und Maschinellen Lernverfahren bei Fragestellungen des Finanzbereichs und quantitativen Methoden zur Beurteilung von Markt- und Länderrisiken. Das Spektrum ausgewählter Referate in diesem Buch, u.a. auch von international renommierten Experten, reicht von allgemeinen Betrachtungen zur Prognose mit Neuronalen Netzen und empirischen Ergebnissen für Wechselkurse, Rentenmärkte und Absatzzahlen über die Beurteilung von Marktrisiken und die Kreditüberwachung mit Maschinellen Lernverfahren bis zur Ermittlung und Einschätzung von Länderrisiken. Dieser Band berichtet über die aktuelle Entwicklung in diesen Gebieten und bietet ein Forum für Diskussionen.

Advances in Mining Graphs, Trees and Sequences

Advances in Mining Graphs, Trees and Sequences PDF Author: Takashi Washio
Publisher: IOS Press
ISBN: 9781586035280
Category : Computers
Languages : en
Pages : 224
Book Description
Ever since the early days of machine learning and data mining, it has been realized that the traditional attribute-value and item-set representations are too limited for many practical applications in domains such as chemistry, biology, network analysis and text mining. This has triggered a lot of research on mining and learning within alternative and more expressive representation formalisms such as computational logic, relational algebra, graphs, trees and sequences. The motivation for using graphs, trees and sequences. Is that they are 1) more expressive than flat representations, and 2) potentially more efficient than multi-relational learning and mining techniques. At the same time, the data structures of graphs, trees and sequences are among the best understood and most widely applied representations within computer science. Thus these representations offer ideal opportunities for developing interesting contributions in data mining and machine learning that are both theoretically well-founded and widely applicable. The goal of this book is to collect recent outstanding studies on mining and learning within graphs, trees and sequences in studies worldwide.

Advanced Data Mining and Applications

Advanced Data Mining and Applications PDF Author: Xudong Luo
Publisher: Springer
ISBN: 331914717X
Category : Computers
Languages : en
Pages : 741
Book Description
This book constitutes the proceedings of the 10th International Conference on Advanced Data Mining and Applications, ADMA 2014, held in Guilin, China during December 2014. The 48 regular papers and 10 workshop papers presented in this volume were carefully reviewed and selected from 90 submissions. They deal with the following topics: data mining, social network and social media, recommend systems, database, dimensionality reduction, advance machine learning techniques, classification, big data and applications, clustering methods, machine learning, and data mining and database.

Emerging Technologies in Data Mining and Information Security

Emerging Technologies in Data Mining and Information Security PDF Author: Ajith Abraham
Publisher: Springer
ISBN: 9811314985
Category : Technology & Engineering
Languages : en
Pages : 885
Book Description
The book features research papers presented at the International Conference on Emerging Technologies in Data Mining and Information Security (IEMIS 2018) held at the University of Engineering & Management, Kolkata, India, on February 23–25, 2018. It comprises high-quality research by academics and industrial experts in the field of computing and communication, including full-length papers, research-in-progress papers, case studies related to all the areas of data mining, machine learning, IoT and information security.