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Linear SVM for complex dataset

In this exercise you will build a default cost linear SVM for the complex dataset you created in the first lesson of this chapter. You will also calculate the training and test accuracies and plot the classification boundary against the test dataset. The e1071 library has been loaded, and test and training datasets have been created for you and are available in the data frames trainset and testset.

This exercise is part of the course

Support Vector Machines in R

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Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

#build model
svm_model<- 
    svm(y ~ ., data = ___, type = "C-classification", 
        kernel = ___)
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