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This repository has been archived by the owner on Oct 12, 2020. It is now read-only.
When you have different parameters that are varying, when you compare many methods and when you want to keep all the results of an analysis, your code can become quite complex.
In this tutorial, we'll make a comparison of machine learning methods for predicting disease based on small SNP data. We'll show how to use the tidyverse set of packages to make the analysis easier by using consistent data structures and functional programming. We'll use tibbles with list-columns.
How do you store results of an analysis?
When you have different parameters that are varying, when you compare many methods and when you want to keep all the results of an analysis, your code can become quite complex.
In this tutorial, we'll make a comparison of machine learning methods for predicting disease based on small SNP data. We'll show how to use the tidyverse set of packages to make the analysis easier by using consistent data structures and functional programming. We'll use tibbles with list-columns.
You can find the first version of the tuto there
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