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Introduction

In: Applied Predictive Modeling

Author

Listed:
  • Max Kuhn

    (Pfizer Global Research and Development, Division of Nonclinical Statistics)

  • Kjell Johnson

    (Arbor Analytics)

Abstract

Every day people are faced with questions such as “What route should I take to work today?” “Should I switch to a different cell phone carrier?” “How should I invest my money?” or “Will I get cancer?” These questions indicate our desire to know future events, and we earnestly want to make the best decisions towards that future. In this chapter we explore the contrast between the competing modeling objectives of prediction and interpretation (Section 1.1), outline the foundational components for developing predictive models (Section 1.2) and define common terminology (Section 1.3), and provide summaries of data sets that will be used throughout the book (Section 1.4). The chapter ends with an overview of the four parts of the book (Section 1.5), and notation used throughout the text (Section 1.6).

Suggested Citation

  • Max Kuhn & Kjell Johnson, 2013. "Introduction," Springer Books, in: Applied Predictive Modeling, chapter 0, pages 1-16, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4614-6849-3_1
    DOI: 10.1007/978-1-4614-6849-3_1
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