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Mastering Predictive Analytics with scikit-learn and TensorFlow

You're reading from   Mastering Predictive Analytics with scikit-learn and TensorFlow Implement machine learning techniques to build advanced predictive models using Python

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Product type Paperback
Published in Sep 2018
Publisher Packt
ISBN-13 9781789617740
Length 154 pages
Edition 1st Edition
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Author (1):
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Alvaro Fuentes Alvaro Fuentes
Author Profile Icon Alvaro Fuentes
Alvaro Fuentes
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Improving models with feature engineering

Now that we have seen how feature engineering techniques help in building predictive models, let's try and improve the performance of these models and evaluate whether the newly built model works better than the previous built model. Then, we will talk about two very important concepts that you must always keep in mind when doing predictive analytics, and these are the reducible and irreducible errors in your predictive models.

Let's first import the necessary modules, as shown in the following screenshot:

So, let's go to the Jupyter Notebook and take a look at the imported credit card default dataset that we saw earlier in this chapter, but as you can see, some modifications have been made to this dataset:

For this model, instead of transforming the sex and marriage features into two dummy features, the ones that we have...

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