Introduction to Predictive Analytics
Introduction to Predictive Analytics
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预测分析简介
DOI：
10.1007/978-3-030-14038-0_1
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
L. Halawi
中科院分区：
文献类型：
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作者：
Richard V. McCarthy;Mary M. McCarthy;Wendy Ceccucci;L. Halawi
很少有技术能够彻底改变企业的运作方式。预测分析就是其中之一。预测分析主要由“三大”技术组成：回归分析、决策树和神经网络。尽管随机森林和集成模型等其他技术的使用越来越流行，但预测分析侧重于构建和评估预测模型，从而产生用于解决业务问题的关键输出拟合统计数据。本章定义了基本的分析术语，介绍了构建预测分析模型的九步流程，介绍了“三大”技术，并讨论了业务分析领域的职业。
There are few technologies that have the ability to revolutionize how business operates. Predictive analytics is one of those technologies. Predictive analytics consists primarily of the “Big 3” techniques: regression analysis, decision trees, and neural networks. Although several other techniques, such as random forests and ensemble models, have become increasingly popular in their use, predictive analytics focuses on building and evaluating predictive 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.