Abstract
This chapter provides an overview of the descriptive, predictive, and prescriptive analytics landscape. Data mining is first introduced, followed by coverage of the role of machine learning and artificial intelligence in analytics. Supervised and unsupervised learning are compared, along with the different applications that fall under each. The characteristics and role of reports in descriptive analytics are described, along with the extraction of data in a multidimensional environment. Key algorithms, covering different predictive analytics applications, are described in some detail.
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El Morr, C., Ali-Hassan, H. (2019). Descriptive, Predictive, and Prescriptive Analytics. In: Analytics in Healthcare. SpringerBriefs in Health Care Management and Economics. Springer, Cham. https://doi.org/10.1007/978-3-030-04506-7_3
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DOI: https://doi.org/10.1007/978-3-030-04506-7_3
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