Visualizing support vectors using ggplot
In this exercise you will plot the training dataset you used to build a linear SVM and mark out the support vectors. The training dataset has been preloaded for you in the dataframe trainset and the SVM model is stored in the variable svm_model.
This exercise is part of the course
Support Vector Machines in R
Exercise instructions
- Load
ggplot2. - Plot the training dataset.
- Mark out the support vectors on the plot using their indices from the SVM model.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
#load ggplot
library(ggplot2)
#build scatter plot of training dataset
scatter_plot <- ggplot(data = ___, aes(x = x1, y = x2, color = y)) +
geom_point() +
scale_color_manual(values = c("red", "blue"))
#add plot layer marking out the support vectors
layered_plot <-
scatter_plot + geom_point(data = trainset[svm_model$___, ], aes(x = x1, y = x2), color = "purple", size = 4, alpha = 0.5)
#display plot
layered_plot