Prediction Modeling Methodology

Frank J. W. M. Dankers; Alberto Traverso; Leonard Wee; Sander M. J. van Kuijk

doi:10.1007/978-3-319-99713-1_8

Prediction Modeling Methodology

Review

In: Fundamentals of Clinical Data Science [Internet]. Cham (CH): Springer; 2019. Chapter 8.

2018 Dec 22.

Authors

Frank J. W. M. Dankers^{1

2}, Alberto Traverso¹, Leonard Wee¹, Sander M. J. van Kuijk³

Book Editors

Pieter Kubben¹, Michel Dumontier², Andre Dekker³

Affiliations

¹ Department of Radiation Oncology (MAASTRO), GROW School of Oncology and Developmental Biology (GROW), Maastricht University Medical Center, Maastricht, The Netherlands
² Department of Radiation Oncology, Radboud University Medical Center, Nijmegen, The Netherlands
³ Department of Clinical Epidemiology and Medical Technology Assessment (KEMTA), Maastricht University Medical Center, Maastricht, The Netherlands

Book Affiliations

¹ Department of Neurosurgery, Maastricht University, Maastricht, Limburg, The Netherlands
² Institute of Data Science, Maastricht University, Maastricht, Limburg, The Netherlands
³ Maastro Clinic, Maastricht, Limburg, The Netherlands

Excerpt

In the previous chapter, you have learned how to prepare your data before you start the process of generating a predictive model. In this chapter, you will learn how to make a predictive model using very common regression techniques and how to evaluate the performance of a model. In the next chapter we will then look at more advanced machine learning techniques that have become increasingly popular in recent years.

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