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Test-Driven Machine Learning by Justin Bozonier

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Summary

We covered a lot of material in this chapter. Once again, we covered moving incrementally in small steps in order to get specific software built. We also leveraged OOP to enable us to test our ClassifierChooser in isolation from our complex machine learning algorithms. Beyond this, we even leveraged creating extremely simple test classifiers to act as our way of decoupling from the more complex algorithms.

We now have the beginnings of a system that can test machine learning algorithms, and choose the best one according to some metric. We've also established a pattern to bring outside algorithms into our project, which includes wrapping the external library in an adapter. This ensures that you can bend the third-party library to your needs ...

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