Visualizing decision & margin bounds using `ggplot2`
In this exercise, you will add the decision and margin boundaries to the support vector scatter plot created in the previous exercise. The SVM model is available in the variable svm_model
and the weight vector has been precalculated for you and is available in the variable w
. The ggplot2
library has also been preloaded.
This exercise is part of the course
Support Vector Machines in R
Exercise instructions
- Calculate the slope and intercept of the decision boundary.
- Add the decision boundary to the plot.
- Add the margin boundaries to the plot.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
#calculate slope and intercept of decision boundary from weight vector and svm model
slope_1 <- -___/w[2]
intercept_1 <- ___$rho/w[2]
#build scatter plot of training dataset
scatter_plot <- ggplot(data = trainset, aes(x = x1, y = x2, color = y)) +
geom_point() + scale_color_manual(values = c("red", "blue"))
#add decision boundary
plot_decision <- scatter_plot + ___(slope = ___, intercept = ___)
#add margin boundaries
plot_margins <- plot_decision +
___(slope = ___, intercept = ___ - 1/w[2], linetype = "dashed")+
___(slope = ___, intercept = ___ + 1/w[2], linetype = "dashed")
#display plot
plot_margins