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• Sales Rank: #1711733 in Books
• Published on: 1992-11-28
• Number of items: 2
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ASWB is a registered service mark of the Association of Social Work Boards, which neither sponsors nor endorses this product.

• Sales Rank: #8091 in Books
• Published on: 2015-05-11
• Original language: English
• Number of items: 1
• Dimensions: 11.00" h x .80" w x 8.50" l, .0 pounds
• Binding: Paperback
• 352 pages

About the Author

Dawn Apgar, PhD, LSW, ACSW, has helped thousands of social workers across the country pass the examinations associated with all levels of licensure. In recent years, she has consulted in numerous states to assist with establishing licensure test preparation programs, including training the instructors.

Dr. Apgar has done research on licensure funded by the American Foundation for Research and Consumer Education in Social Work Regulation and is currently chairperson of her state's social work licensing board. She is a past President of the New Jersey Chapter of NASW and has been on its National Board of Directors. In 2014, the Chapter presented her with a Lifetime Achievement Award. Dr. Apgar has taught in both undergraduate and graduate social work programs and has extensive direct practice, policy, and management experience in the field.

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Product details

Hardcover: 720 pages

Publisher: Waveland Pr Inc; 3 edition (August 31, 2011)

Language: English

ISBN-10: 1577667395

ISBN-13: 978-1577667391

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• Sales Rank: #850450 in Books
• Published on: 2013-12-18
• Original language: English
• Number of items: 1
• Dimensions: 10.00" h x .69" w x 7.99" l, .0 pounds
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• Sales Rank: #2132977 in eBooks
• Published on: 2015-02-26
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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. The book

• 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

• Sales Rank: #989979 in Books
• Brand: Brand: Academic Press
• Published on: 2013-12-26
• Original language: English
• Number of items: 1
• Dimensions: 9.25" h x 1.06" w x 7.52" l, 2.55 pounds
• Binding: Hardcover
• 514 pages

• Used Book in Good Condition

Review

"The book contains a wealth of modern material that should be covered in more depth in statistics courses: for example, missing data, outlier detection, missing imputation, correlation coefficient matrices, principles of model selection, text mining, and decision trees…The book has many hot and recent packages; many are written or have theory based on results developed since 2010."--MAA.org, April 23, 2014 "Zhao and Cen present 15 real-world applications of data mining with the open-source statistics software R. Each application covers the business background, and problems, data extraction and exploitation, data preprocessing, modeling, model evaluation, findings, and model deployment. They involve a diverse set of challenging problems in terms of data size, data type, data mining goals, and the methodologies and tools to carry out the analysis."--ProtoView.com, February 2014

From the Author
This book presents 15 real-world applications on data mining with R. Each application is presented as one chapter, covering business background and problems, data extraction and exploration, data preprocessing, modeling, model evaluation, findings and model deployment.
 
R code, Data and color figures for the book are provided at the RDataMining.com website.

Table of Contents

• Foreword
  Graham Williams

• Chapter 1 Power Grid Data Analysis with R and Hadoop
  Terence Critchlow, Ryan Hafen, Tara Gibson and Kerstin Kleese van Dam

• Chapter 2 Picturing Bayesian Classifiers: A Visual Data Mining Approach to Parameters Optimization
  Giorgio Maria Di Nunzio and Alessandro Sordoni

• Chapter 3 Discovery of emergent issues and controversies in Anthropology using text mining, topic modeling and social network analysis of microblog content
  Ben Marwick

• Chapter 4 Text Mining and Network Analysis of Digital Libraries in R
  Eric Nguyen

• Chapter 5 Recommendation systems in R
  Saurabh Bhatnagar

• Chapter 6 Response Modeling in Direct Marketing: A Data Mining Based Approach for Target Selection
  Sadaf Hossein Javaheri, Mohammad Mehdi Sepehri and Babak Teimourpour

• Chapter 7 Caravan Insurance Policy Customer Profile Modeling with R Mining
  Mukesh Patel and Mudit Gupta

• Chapter 8 Selecting Best Features for Predicting Bank Loan Default
  Zahra Yazdani, Mohammad Mehdi Sepehri and Babak Teimourpour

• Chapter 9 A Choquet Ingtegral Toolbox and its Application in Customer's Preference Analysis
  Huy Quan Vu, Gleb Beliakov and Gang Li

• Chapter 10 A Real-Time Property Value Index based on Web Data
  Fernando Tusell, Maria Blanca Palacios, María Jesús Bárcena and Patricia Menéndez

• Chapter 11 Predicting Seabed Hardness Using Random Forest in R
  Jin Li, Justy Siwabessy, Zhi Huang, Maggie Tran and Andrew Heap

• Chapter 12 Supervised classification of images, applied to plankton samples using R and zooimage
  Kevin Denis and Philippe Grosjean

• Chapter 13 Crime analyses using R
  Madhav Kumar, Anindya Sengupta and Shreyes Upadhyay

• Chapter 14 Football Mining with R
  Maurizio Carpita, Marco Sandri, Anna Simonetto and Paola Zuccolotto

• Chapter 15 Analyzing Internet DNS(SEC) Traffic with R for Resolving Platform Optimization
  Emmanuel Herbert, Daniel Migault, Stephane Senecal, Stanislas Francfort and Maryline Laurent

From the Back Cover
Data Mining Applications with R is a great resource for researchers and professionals to understand the wide use of R in solving different problems in industry. Fifteen different real world case studies in hot topic areas are presented offering various techniques from experts in the field. With R becoming the most popular and widely used statistical software in learning data mining techniques across many different industries, this book is an essential resource for data mining researchers in academia and industry looking for ways to turn this versatile software into a powerful analytic tool.

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