Prediction Modeling Methodology

Frank Dankers; Alberto Traverso; Leonard Wee; Sander van Kuijk

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

Prediction Modeling Methodology

Frank Dankers^*, Alberto Traverso, Leonard Wee, Sander van Kuijk

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Chapter › Academic

Abstract

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.

Original language	English
Title of host publication	Fundamentals of Clinical Data Science
Editors	Pieters Kubben, Michel Dumontier, Andre Dekker
Publisher	Springer
Chapter	8
Pages	101-120
Number of pages	20
ISBN (Electronic)	978-3-319-99713-1
ISBN (Print)	978-3-319-99712-4
DOIs	https://doi.org/10.1007/978-3-319-99713-1_8
Publication status	Published - 2019

Access to Document

10.1007/978-3-319-99713-1_8Licence: CC BY

Cite this

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abstract = "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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