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Titlebook: Applying Predictive Analytics; Finding Value in Dat Richard V. McCarthy,Mary M. McCarthy,Wendy Ceccucc Textbook 2022Latest edition The Edit

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期刊全称Applying Predictive Analytics
期刊简称Finding Value in Dat
影响因子2023Richard V. McCarthy,Mary M. McCarthy,Wendy Ceccucc
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发行地址Focuses on how to use predictive analytic techniques to analyze historical data.An applied approach and focus on solving business problems using predictive analytics.Uses examples in SAS Enterprise Mi
图书封面Titlebook: Applying Predictive Analytics; Finding Value in Dat Richard V. McCarthy,Mary M. McCarthy,Wendy Ceccucc Textbook 2022Latest edition The Edit
影响因子.The new edition of this textbook presents a practical, updated approach to predictive analytics for classroom learning. The authors focus on using analytics to solve business problems and compares several different modeling techniques, all explained from examples using the SAS Enterprise Miner software. The authors demystify complex algorithms to show how they can be utilized and explained within the context of enhancing business opportunities. Each chapter includes an opening vignette that provides real-life examples of how business analytics have been used in various aspects of organizations to solve issues or improve their results. A running case provides an example of a how to build and analyze a complex analytics model and utilize it to predict future outcomes. The new edition includes chapters on clusters and associations and text mining to support predictive models. An additional case is also included that can be used with each chapter or as a semester project..
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Finding Associations in Data Through Cluster Analysis,in the same cluster. In this chapter several clustering techniques are explained. A simple example is used to explain the different clustering methods. Finally, clustering is applied to a subset of the automobile insurance data set.
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https://doi.org/10.1007/978-3-030-71644-8dictive models resulting in key output fit statistics that are used to solve business problems. This chapter defines essential analytics terminology, walks through the nine-step process for building predictive analytics models, introduces the “Big 3” techniques, and discusses careers within business analytics.
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