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Test-Driven Machine Learning
book

Test-Driven Machine Learning

by Justin Bozonier
November 2015
Intermediate to advanced content levelIntermediate to advanced
190 pages
4h 11m
English
Packt Publishing
Content preview from Test-Driven Machine Learning

The real world

Now that we have this harness built that can make recommendations on the customers that we should advertise to, we need to think about the kind of algorithms that we want to plug in it. For the probability of a customer placing an order, we can use Logistic Regression or Naïve Bayes. To estimate how much money the customer might spend, we can use (depending on our data) Gaussian Naïve Bayes or Linear Regression.

To start off with, let's use Linear Regression and Logistic Regression. The main purpose of doing this is to use more sklearn as, if we do, we won't have to spend time building the algorithms ourselves.

When we begin, it may be helpful to create a test file just to explore sklearn like in the previous chapter. We already have ...

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Publisher Resources

ISBN: 9781784399085Supplemental Content