This project is about over-fitting and it is based on chapter 6 Statistical Mach

This project is about over-fitting and it is based on chapter 6 Statistical Machine Learning from ‘Practical Statistics for Data Scientists’.
Files needed:
P4p4F1.pdf P4p4F1.pdf – Alternative Formats
P4p4F2.pdf P4p4F2.pdf – Alternative Formats
P4p4F3.pdf P4p4F3.pdf – Alternative Formats
Cover in the project the following:
Explain the data from figure P4p4F1.pdf.
Explain the differences in (a) and (b) parts in figure P4p4F2.pdf.
Try to recreate with R or Octave, as close as possible, the data from the figure P4p4F1.pdf. Functions needed are: runif (R) rand (Octave) for uniform distribution and rnorm (R) randn() (Octave) for the normal distributionexplain how you can recreate P4p4F1.pdf
compare and discuss my P4p4F3.pdf with the figure you created
Based on the P4p4F3.pdf, or your data created, explain how you would make a decision tree to classify ‘+’ and ‘o’ similarly to the way it was done in the left tree in P4p2F2.pdf
In your opinion, why is it practical or useful to simulate the data for the classification?