Statistical learning with R: 2017 edition
New year, new class (with a brand new name!), and a whole bunch of new R demos. If you have not played with R yet, the notes I have attached to the introductory Lab might be of help.
If you attended the class, you probably know what to do with the next posts. After you have ran each demo, answer the related questions you might find both in the blog post and in the demo itself. Add whatever is necessary (screenshots, code, text, links) to motivate your answers and convince me you actually ran the demos and understood their contents. Finally send me everything in a pdf file.
To run each demo, just open the R file you will find in each post with the source command in R, for example:
source("/whatever/your/path/is/demofilename.R",print.eval = TRUE)
For your convenience, here is a package containing all of the source and data files you need for your homework (the package will be updated every time a new demo is added). Remember that while you will not be asked to add much new code to the demos, you should at least be able to understand what the existing code does and modify some parameters to produce different results. Now feel free to play with the following demos:
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