R Data Mining Blueprints

Product Description
Learn about data mining with real-world projects
About This Book

Solve predictive modeling problems using the most popular data mining algorithms
Practical and focused on real-world data mining projects, this book covers concepts such as spatial data mining, text mining, social media mining, and web mining
Real-world case studies illustrate various data mining techniques, taking you from novice to intermediate

Who This Book Is For
Data analysts from beginners to intermediate level who need a step by step helping hand in developing complex data mining projects. They have prior knowledge about basic statistics and little bit of programming language experience in any tool or platform. They ideally would have worked with R before and are now interested in exploring data mining in more depth and in different domains.
What You Will Learn

Gain knowledge on the new programming interface-R
Execute models and identify performance indicators
Compare various alternative techniques
Implement all the models using R
Validate and integrate the models developed in R
Develop and deploy advanced models in data mining with R

In Detail
The R language is a powerful open source functional programming language. At its core, R is a statistical programming language that provides impressive tools for data mining and analysis. It enables you to create high-level graphics and offers an interface to other languages. This means R is best suited to produce data and visual analytics through customization scripts and commands, instead of the typical statistical tools that provide tick boxes and drop-down menus for users.
This book explores data mining techniques and shows you how to apply different mining concepts to various statistical and data applications in a wide range of fields. We will teach you about R and its application to data mining, and give you relevant and useful information you can use to develop and improve your applications. It will help you complete complex data mining projects and guide you through handling issues you might encounter during projects.
About the Author
Pradeepta Mishra is a data mining and predictive analytics professional with a total of 9 years experience mostly in the area of statistical modeling. He is an intermediate practitioner in machine learning, text mining, and sentiment analysis. He filed a patent as the lead inventor (India and the U.S.) for developing a new algorithm to address the issues in assortment optimization and store space planning based on linear and non-Linear product substitutions. He is specialized in the domain of forecasting linear, non-linear, and ensembles including complex forecasting algorithms for time series data. He has the ability to understand and implement complex algorithms such as neural network, support vector machine, and machine learning in advanced predictive analytics.