Test-Driven Machine Learning

Planning our journey

TDD is a way to incrementally design our code, but this doesn't mean that we can stop thinking about it. Getting some idea of how we want to approach the problem can actually be quite useful, as long as we're prepared to leave behind our preconceptions if it doesn't prove to be a testable design.

Let's take a moment to review the Naïve Bayes and Random Forest classifiers. What are the methods/functions that they have in common? It looks like batch_train and classify have the same signature, and both appear on both classes. Python doesn't have the concept of interfaces similar to what Java or C# have, but if it did have, we might have an interface that would look like the following:

class Classifier: def batch_train(self, observations): ...