Training Sets, Test Sets, R, and ggplot – Free Udemy Courses
How to evaluate regression model performance in R
What you’ll learn
Training Sets, Test Sets, R, and ggplot – Free Udemy Courses
- randomly divide a data set into a training set and a test set
- calculate the test MSE (mean squared error)
- calculate quickly the MSE for several models
- visualize the variability of the MSE with ggplot
- row-slice data frames
- use R’s predict function
- write for loops in R
- write functions of two variables in R
- combine functions and for loops
- add titles and labels to plots in ggplot
Requirements
-
The students must have the background one would get by viewing my two Udemy courses on linear and polynomial regression.
-
Students will need to have R and RStudio installed on their computers.
Description
In this course, I show you how to evaluate the performance of a regression model using training sets and test sets. We will use R and ggplot as our tools. Along the way, we will learn how to row-slice data frames, use the predict function in R, and add titles and labels to our plots. We will also work on our programming skills by learning how to write for loops and functions of two variables.
Students should have a background in R, ggplot, and regression equivalent to what one would have after viewing my two Udemy courses on linear and polynomial regression. At a relaxed pace, it should take about two weeks to complete the course.
Who this course is for:
- This course is for those looking to improve their R programming skills.
- This course is for those with a background equivalent to what one would have after viewing my first two Udemy courses in linear and polynomial regression.
If the links does not work, contact us we will fix them
Add Comment