Data mining and predictive analytics book
Data Mining and Predictive Analytics, 2nd Edition [Book]Put Predictive Analytics into Action Learn the basics of Predictive Analysis and Data Mining through an easy to understand conceptual framework and immediately practice the concepts learned using the open source RapidMiner tool. Whether you are brand new to Data Mining or working on your tenth project, this book will show you how to analyze data, uncover hidden patterns and relationships to aid important decisions and predictions. Data Mining has become an essential tool for any enterprise that collects, stores and processes data as part of its operations. This book is ideal for business users, data analysts, business analysts, business intelligence and data warehousing professionals and for anyone who wants to learn Data Mining. Gain the necessary knowledge of different data mining techniques, so that you can select the right technique for a given data problem and create a general purpose analytics process.
Predictive analytics for marketers : using data mining for business advantage (book)
In sum, the 31 chapters of simple yet insightful quantitative techniques make this book unique in the field of data mining literature. Hypothesis Testing As opposed to traditional hypothesis testing designed to verify a precictive hypotheses about relations between variables e. Descriptive Statistics 3. After the phase of learning from an existing data set.
New York: Morgan-Kaufman. Get A Copy. For example, when data are collected via automated computerized methods. Data Sets 3.
It seems that you're in Germany. We have a dedicated site for Germany. This in-depth guide provides managers with a solid understanding of data and data trends, the opportunities that it can offer to businesses, and the dangers of these technologies. Written in an accessible style, Steven Finlay provides a contextual roadmap for developing solutions that deliver benefits to organizations. Steven Finlay is one of the UK's leading experts on predictive analytics and its application within Big Data environments. He has extensive experience of developing predictive analytics solutions within Financial Services, Retailing and Government organisations. Previously he has worked as a data scientist, consultant and project manager for a variety of organizations in both the public and private sectors.
Timothy has been named a top global business journalist by Richtopia. It also includes classification modeling. Neural Networks is one of the Data Mining techniques. Request permission to reuse content from this site.
The framework is reinforced with examples and sample datasets that demonstrate how to apply the new tools to real-world problems. For example, where each consecutive classifier in the sequence is an "expert" in classifying observations that were not well classified by those preceding it. Instructor View Instructor Companion Site. Boosting will generate a sequence of classifiers, one of many applications of the brushing technique is to select i.