Exercise

RBF SVM on a complex dataset

Calculate the average accuracy for a RBF kernel SVM using 100 different training/test partitions of the complex dataset you generated in the first lesson of this chapter. Use default settings for the parameters. The e1071 library has been preloaded and the dataset is available in the dataframe df. Use random 80/20 splits of the data in df when creating training and test datasets for each iteration.

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Create a vector of length 100 to hold accuracies for each step.