Visualizing an SVM fit
To visualize the built model, one can first use the plot function to generate a scatter plot of data input and the SVM fit. In this plot, support vectors and classes are highlighted through the color symbol. In addition to this, one can draw a contour filled plot of the class regions to easily identify misclassified samples from the plot.
Getting ready
In this recipe, we will use two datasets: the iris dataset and the telecom churn dataset. For the telecom churn dataset, one needs to have completed the previous recipe by training a support vector machine with SVM, and to have saved the SVM fit model.
How to do it...
Perform the following steps to visualize the SVM fit object:
- Use SVM to train the support vector machine based ...
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