R Data Mining Blueprints

R Data Mining Blueprints

作者: Pradeepta Mishra
出版社: Packt Publishing
出版在: 2016-07-29
ISBN-13: 9781783989683
ISBN-10: 1783989688
裝訂格式: Paperback
總頁數: 260 頁





內容描述


Learn about data mining with real-world projectsAbout This BookSolve predictive modeling problems using the most popular data mining algorithmsPractical and focused on real-world data mining projects, this book covers concepts such as spatial data mining, text mining, social media mining, and web miningReal-world case studies illustrate various data mining techniques, taking you from novice to intermediateWho This Book Is ForData 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 LearnGain knowledge on the new programming interface-RExecute models and identify performance indicatorsCompare various alternative techniquesImplement all the models using RValidate and integrate the models developed in RDevelop and deploy advanced models in data mining with RIn DetailThe 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.




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