us is it gives us the ability to sample different functions with only a few data points such as linear functions sinusoid functions but they were inherently ambiguous because there's some noise in the data as well as represent different classification problems for different classifiers with different decision boundaries as again shown in the colored dashed lines and perhaps most importantly it's also it's better able to model ambiguous future learning problems like I showed on the first slide okay for further reading on