Machine Learning with R Cookbook - Second Edition

How to do it...

Perform the following steps to visualize the SVM fit object:

1. Use SVM to train the support vector machine based on the iris dataset and use the plot function to visualize the fitted model:

        > data(iris)
        > model.iris  = svm(Species~., iris)
        > plot(model.iris, iris, Petal.Width ~ Petal.Length, slice =        list(Sepal.Width        = 3, Sepal.Length = 4))

The SVM classification plot of trained SVM fit based on iris dataset

2. Visualize the SVM fit object, model, using the plot function with the dimensions of total_day_minutes and total_intl_charge:

        > plot(model, trainset, total_day_minutes ~ total_intl_charge)

The SVM classification plot ...