Machine Learning with R Cookbook - Second Edition

How to do it...

Perform the following steps to generate a classification measurement:

1. Train an svm model using the training dataset:

        > svm.model= train(churn ~ .,
        +                   data = trainset,
        +                   method = "svmRadial")  

2. You can then predict labels using the fitted model, svm.model:

        > svm.pred = predict(svm.model, testset[,! names(testset)        %in% c("churn")])

3. Next, you can generate a classification table:

        > table(svm.pred, testset[,c("churn")])
    
        Output
        svm.pred yes  no
             yes  73  16
             no   68 861  

4. Lastly, you can generate a confusion matrix using the prediction results and the actual labels from the testing dataset:

 > confusionMatrix(svm.pred, testset[,c("churn")]) Output Confusion Matrix and Statistics Reference Prediction yes no yes 73 16 no 68 861 Accuracy ...