Data Mining Applications with R

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  • Author : Yanchang Zhao
  • Publisher : Academic Press
  • Pages : 514 pages
  • ISBN : 0124115209
  • Rating : 4.5/5 from 3 reviews
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Download or Read online Data Mining Applications with R full in PDF, ePub and kindle. this book written by Yanchang Zhao and published by Academic Press which was released on 26 November 2013 with total page 514 pages. We cannot guarantee that Data Mining Applications with R book is available in the library, click Get Book button and read full online book in your kindle, tablet, IPAD, PC or mobile whenever and wherever You Like. 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

Data Mining Applications with R

Data Mining Applications with R
  • Author : Yanchang Zhao,Yonghua Cen
  • Publisher : Academic Press
  • Release : 26 November 2013
GET THIS BOOK Data Mining Applications with R

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

R and Data Mining

R and Data Mining
  • Author : Yanchang Zhao
  • Publisher : Academic Press
  • Release : 31 December 2012
GET THIS BOOK R and Data Mining

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,

Classification Clustering and Data Mining Applications

Classification  Clustering  and Data Mining Applications
  • Author : David Banks,Leanna House,Frederick R. McMorris,Phipps Arabie,Wolfgang A. Gaul
  • Publisher : Springer Science & Business Media
  • Release : 07 January 2011
GET THIS BOOK Classification Clustering and Data Mining Applications

This volume describes new methods with special emphasis on classification and cluster analysis. These methods are applied to problems in information retrieval, phylogeny, medical diagnosis, microarrays, and other active research areas.

Data Mining for Business Analytics

Data Mining for Business Analytics
  • Author : Galit Shmueli,Peter C. Bruce,Peter Gedeck,Nitin R. Patel
  • Publisher : John Wiley & Sons
  • Release : 05 November 2019
GET THIS BOOK Data Mining for Business Analytics

Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python presents an applied approach to data mining concepts and methods, using Python software for illustration Readers will learn how to implement a variety of popular data mining algorithms in Python (a free and open-source software) to tackle business problems and opportunities. This is the sixth version of this successful text, and the first using Python. It covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction,

Data Mining for Scientific and Engineering Applications

Data Mining for Scientific and Engineering Applications
  • Author : R.L. Grossman,C. Kamath,P. Kegelmeyer,V. Kumar,R. Namburu
  • Publisher : Springer Science & Business Media
  • Release : 01 December 2013
GET THIS BOOK Data Mining for Scientific and Engineering Applications

Advances in technology are making massive data sets common in many scientific disciplines, such as astronomy, medical imaging, bio-informatics, combinatorial chemistry, remote sensing, and physics. To find useful information in these data sets, scientists and engineers are turning to data mining techniques. This book is a collection of papers based on the first two in a series of workshops on mining scientific datasets. It illustrates the diversity of problems and application areas that can benefit from data mining, as well

Data Mining for Business Analytics

Data Mining for Business Analytics
  • Author : Galit Shmueli,Peter C. Bruce,Nitin R. Patel
  • Publisher : John Wiley & Sons
  • Release : 18 April 2016
GET THIS BOOK Data Mining for Business Analytics

Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner®, Third Edition presents an applied approach to data mining and predictive analytics with clear exposition, hands-on exercises, and real-life case studies. Readers will work with all of the standard data mining methods using the Microsoft® Office Excel® add-in XLMiner® to develop predictive models and learn how to obtain business value from Big Data. Featuring updated topical coverage on text mining, social network analysis, collaborative filtering, ensemble methods, uplift modeling

Real World Data Mining Applications

Real World Data Mining Applications
  • Author : Mahmoud Abou-Nasr,Stefan Lessmann,Robert Stahlbock,Gary M. Weiss
  • Publisher : Springer
  • Release : 26 November 2014
GET THIS BOOK Real World Data Mining Applications

Data mining applications range from commercial to social domains, with novel applications appearing swiftly; for example, within the context of social networks. The expanding application sphere and social reach of advanced data mining raise pertinent issues of privacy and security. Present-day data mining is a progressive multidisciplinary endeavor. This inter- and multidisciplinary approach is well reflected within the field of information systems. The information systems research addresses software and hardware requirements for supporting computationally and data-intensive applications. Furthermore, it encompasses

R Data Mining

R Data Mining
  • Author : Andrea Cirillo
  • Publisher : Packt Publishing Ltd
  • Release : 29 November 2017
GET THIS BOOK R Data Mining

Mine valuable insights from your data using popular tools and techniques in R About This Book Understand the basics of data mining and why R is a perfect tool for it. Manipulate your data using popular R packages such as ggplot2, dplyr, and so on to gather valuable business insights from it. Apply effective data mining models to perform regression and classification tasks. Who This Book Is For If you are a budding data scientist, or a data analyst with

Mastering Text Mining with R

Mastering Text Mining with R
  • Author : Ashish Kumar,Avinash Paul
  • Publisher : Packt Publishing Ltd
  • Release : 28 December 2016
GET THIS BOOK Mastering Text Mining with R

Master text-taming techniques and build effective text-processing applications with R About This Book Develop all the relevant skills for building text-mining apps with R with this easy-to-follow guide Gain in-depth understanding of the text mining process with lucid implementation in the R language Example-rich guide that lets you gain high-quality information from text data Who This Book Is For If you are an R programmer, analyst, or data scientist who wants to gain experience in performing text data mining and

RapidMiner

RapidMiner
  • Author : Markus Hofmann,Ralf Klinkenberg
  • Publisher : CRC Press
  • Release : 25 October 2013
GET THIS BOOK RapidMiner

Powerful, Flexible Tools for a Data-Driven World As the data deluge continues in today’s world, the need to master data mining, predictive analytics, and business analytics has never been greater. These techniques and tools provide unprecedented insights into data, enabling better decision making and forecasting, and ultimately the solution of increasingly complex problems. Learn from the Creators of the RapidMiner Software Written by leaders in the data mining community, including the developers of the RapidMiner software, RapidMiner: Data Mining

Advanced Data Mining and Applications

Advanced Data Mining and Applications
  • Author : Reda Alhajj,Hong Gao,Xue Li,Jianzhong Li,Osmar R. Zaiane
  • Publisher : Springer Science & Business Media
  • Release : 17 July 2007
GET THIS BOOK Advanced Data Mining and Applications

This book constitutes the refereed proceedings of the Third International Conference on Advanced Data Mining and Applications, ADMA 2007, held in Harbin, China in August 2007. The papers focus on advancements in data mining and peculiarities and challenges of real world applications using data mining.

Data Mining and Predictive Analytics

Data Mining and Predictive Analytics
  • Author : Daniel T. Larose,Chantal D. Larose
  • Publisher : John Wiley & Sons
  • Release : 16 March 2015
GET THIS BOOK Data Mining and Predictive Analytics

Learn methods of data analysis and their application to real-world data sets. Offers comprehensive coverage of association rules, clustering, neural networks, logistic regression, multivariate analysis, and R statistical programming language Features over 750 chapter exercises, allowing readers to assess their understanding of the new material Provides a detailed case study that brings together the lessons learned in the book Includes access to the companion website, www.dataminingconsultant, with exclusive password-protected instructor content

Basketball Data Science

Basketball Data Science
  • Author : Paola Zuccolotto,Marica Manisera
  • Publisher : CRC Press
  • Release : 21 January 2020
GET THIS BOOK Basketball Data Science

Using data from one season of NBA games, Basketball Data Science: With Applications in R is the perfect book for anyone interested in learning and applying data analytics in basketball. Whether assessing the spatial performance of an MBA player’s shots or doing an analysis of the impact of high pressure game situations on the probability of scoring, this book discusses a variety of case studies and hands-on examples using a custom R package. The codes are supplied so readers

Handbook of Statistical Analysis and Data Mining Applications

Handbook of Statistical Analysis and Data Mining Applications
  • Author : Robert Nisbet,Gary Miner,Ken Yale
  • Publisher : Elsevier
  • Release : 09 November 2017
GET THIS BOOK Handbook of Statistical Analysis and Data Mining Applications

Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. The handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application. This book is an ideal reference for users who want to address massive and