data mining with rattle and r use r

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Data Mining With Rattle And R

Author : Graham Williams
ISBN : 9781441998903
Genre : Mathematics
File Size : 58. 41 MB
Format : PDF, Kindle
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Data mining is the art and science of intelligent data analysis. By building knowledge from information, data mining adds considerable value to the ever increasing stores of electronic data that abound today. In performing data mining many decisions need to be made regarding the choice of methodology, the choice of data, the choice of tools, and the choice of algorithms. Throughout this book the reader is introduced to the basic concepts and some of the more popular algorithms of data mining. With a focus on the hands-on end-to-end process for data mining, Williams guides the reader through various capabilities of the easy to use, free, and open source Rattle Data Mining Software built on the sophisticated R Statistical Software. The focus on doing data mining rather than just reading about data mining is refreshing. The book covers data understanding, data preparation, data refinement, model building, model evaluation, and practical deployment. The reader will learn to rapidly deliver a data mining project using software easily installed for free from the Internet. Coupling Rattle with R delivers a very sophisticated data mining environment with all the power, and more, of the many commercial offerings.

Educational Data Mining With R And Rattle

Author : R. S. Kamath
ISBN : 9788793379312
Genre : Computers
File Size : 82. 6 MB
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Educational Data Mining (EDM) is one of the emerging fields in the pedagogy and andragogy paradigm, it concerns the techniques which research data coming from the educational domain. EDM is a promising discipline which has an imperative impact on predicting students? academic performance. It includes the transformation of existing, and the innovation of new approaches derived from multidisciplinary spheres of influence such as statistics, machine learning, psychometrics, scientific computing etc. An archetype that is covered in this book is that of learning by example. The intention is that reader will easily be able to replicate the given examples and then adapt them to suit their own needs of teaching-learning. The content of the book is based on the research work undertaken by the authors on the theme ?Mining of Educational Data for the Analysis and Prediction of Students? Academic Performance?. The basic know-how presented in this book can be treated as guide for educational data mining implementation using R and Rattle open source data mining tools. Technical topics discussed in the book include: 1- Emerging Research Directions in Educational Data Mining 2- Design Aspects and Developmental Framework of the System 3- Model Development - Building Classifiers 4- Educational Data Analysis: Clustering Approach

R For Business Analytics

Author : A Ohri
ISBN : 9781461443438
Genre : Mathematics
File Size : 74. 56 MB
Format : PDF, Kindle
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R for Business Analytics looks at some of the most common tasks performed by business analysts and helps the user navigate the wealth of information in R and its 4000 packages. With this information the reader can select the packages that can help process the analytical tasks with minimum effort and maximum usefulness. The use of Graphical User Interfaces (GUI) is emphasized in this book to further cut down and bend the famous learning curve in learning R. This book is aimed to help you kick-start with analytics including chapters on data visualization, code examples on web analytics and social media analytics, clustering, regression models, text mining, data mining models and forecasting. The book tries to expose the reader to a breadth of business analytics topics without burying the user in needless depth. The included references and links allow the reader to pursue business analytics topics. This book is aimed at business analysts with basic programming skills for using R for Business Analytics. Note the scope of the book is neither statistical theory nor graduate level research for statistics, but rather it is for business analytics practitioners. Business analytics (BA) refers to the field of exploration and investigation of data generated by businesses. Business Intelligence (BI) is the seamless dissemination of information through the organization, which primarily involves business metrics both past and current for the use of decision support in businesses. Data Mining (DM) is the process of discovering new patterns from large data using algorithms and statistical methods. To differentiate between the three, BI is mostly current reports, BA is models to predict and strategize and DM matches patterns in big data. The R statistical software is the fastest growing analytics platform in the world, and is established in both academia and corporations for robustness, reliability and accuracy. The book utilizes Albert Einstein’s famous remarks on making things as simple as possible, but no simpler. This book will blow the last remaining doubts in your mind about using R in your business environment. Even non-technical users will enjoy the easy-to-use examples. The interviews with creators and corporate users of R make the book very readable. The author firmly believes Isaac Asimov was a better writer in spreading science than any textbook or journal author.

R For Sas And Spss Users

Author : Robert A. Muenchen
ISBN : 0387094180
Genre : Computers
File Size : 25. 15 MB
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While SAS and SPSS have many things in common, R is very different. My goal in writing this book is to help you translate what you know about SAS or SPSS into a working knowledge of R as quickly and easily as possible. I point out how they differ using terminology with which you are familiar, and show you which add-on packages will provide results most like those from SAS or SPSS. I provide many example programs done in SAS, SPSS, and R so that you can see how they compare topic by topic. When finished, you should be able to use R to: Read data from various types of text files and SAS/SPSS datasets. Manage your data through transformations or recodes, as well as splitting, merging and restructuring data sets. Create publication quality graphs including bar, histogram, pie, line, scatter, regression, box, error bar, and interaction plots. Perform the basic types of analyses to measure strength of association and group differences, and be able to know where to turn to cover much more complex methods.

Data Analysis And Graphics Using R

Author : John Maindonald
ISBN : 9781139486675
Genre : Computers
File Size : 53. 74 MB
Format : PDF
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Discover what you can do with R! Introducing the R system, covering standard regression methods, then tackling more advanced topics, this book guides users through the practical, powerful tools that the R system provides. The emphasis is on hands-on analysis, graphical display, and interpretation of data. The many worked examples, from real-world research, are accompanied by commentary on what is done and why. The companion website has code and datasets, allowing readers to reproduce all analyses, along with solutions to selected exercises and updates. Assuming basic statistical knowledge and some experience with data analysis (but not R), the book is ideal for research scientists, final-year undergraduate or graduate-level students of applied statistics, and practising statisticians. It is both for learning and for reference. This third edition expands upon topics such as Bayesian inference for regression, errors in variables, generalized linear mixed models, and random forests.

Data Mining Algorithms

Author : Pawel Cichosz
ISBN : 9781118950807
Genre : Mathematics
File Size : 70. 77 MB
Format : PDF
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Data Mining Algorithms is a practical, technically-oriented guide to data mining algorithms that covers the most important algorithms for building classification, regression, and clustering models, as well as techniques used for attribute selection and transformation, model quality evaluation, and creating model ensembles. The author presents many of the important topics and methodologies widely used in data mining, whilst demonstrating the internal operation and usage of data mining algorithms using examples in R.

Learning R

Author : Richard Cotton
ISBN : 9781449357184
Genre : Computers
File Size : 42. 33 MB
Format : PDF
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Learn how to perform data analysis with the R language and software environment, even if you have little or no programming experience. With the tutorials in this hands-on guide, you’ll learn how to use the essential R tools you need to know to analyze data, including data types and programming concepts. The second half of Learning R shows you real data analysis in action by covering everything from importing data to publishing your results. Each chapter in the book includes a quiz on what you’ve learned, and concludes with exercises, most of which involve writing R code. Write a simple R program, and discover what the language can do Use data types such as vectors, arrays, lists, data frames, and strings Execute code conditionally or repeatedly with branches and loops Apply R add-on packages, and package your own work for others Learn how to clean data you import from a variety of sources Understand data through visualization and summary statistics Use statistical models to pass quantitative judgments about data and make predictions Learn what to do when things go wrong while writing data analysis code

Data Science And Big Data Analytics

Author : EMC Education Services
ISBN : 9781118876053
Genre : Computers
File Size : 31. 91 MB
Format : PDF, Docs
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Data Science and Big Data Analytics is about harnessing the power of data for new insights. The book covers the breadth of activities and methods and tools that Data Scientists use. The content focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with examples that you can replicate using open-source software. This book will help you: Become a contributor on a data science team Deploy a structured lifecycle approach to data analytics problems Apply appropriate analytic techniques and tools to analyzing big data Learn how to tell a compelling story with data to drive business action Prepare for EMC Proven Professional Data Science Certification Corresponding data sets are available at www.wiley.com/go/9781118876138. Get started discovering, analyzing, visualizing, and presenting data in a meaningful way today!

Using R To Unlock The Value Of Big Data Big Data Analytics With Oracle R Enterprise And Oracle R Connector For Hadoop

Author : Mark Hornick
ISBN : 9780071826273
Genre : Computers
File Size : 86. 79 MB
Format : PDF
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The Oracle Press Guide to Big Data Analytics using R Cowritten by members of the Big Data team at Oracle, this Oracle Press book focuses on analyzing data with R while making it scalable using Oracle’s R technologies. Using R to Unlock the Value of Big Data provides an introduction to open source R and describes issues with traditional R and database interaction. The book then offers in-depth coverage of Oracle’s strategic R offerings: Oracle R Enterprise, Oracle R Distribution, ROracle, and Oracle R Connector for Hadoop. You can practice your new skills using the end-of-chapter exercises.

Learning Data Mining With R

Author : Bater Makhabel
ISBN : 9781783982110
Genre : Computers
File Size : 23. 76 MB
Format : PDF, ePub, Docs
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This book is intended for the budding data scientist or quantitative analyst with only a basic exposure to R and statistics. This book assumes familiarity with only the very basics of R, such as the main data types, simple functions, and how to move data around. No prior experience with data mining packages is necessary; however, you should have a basic understanding of data mining concepts and processes.

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