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Applied Supervised Learning with Python

You're reading from   Applied Supervised Learning with Python Use scikit-learn to build predictive models from real-world datasets and prepare yourself for the future of machine learning

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Product type Paperback
Published in Apr 2019
Publisher
ISBN-13 9781789954920
Length 404 pages
Edition 1st Edition
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Authors (2):
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Ishita Mathur Ishita Mathur
Author Profile Icon Ishita Mathur
Ishita Mathur
Benjamin Johnston Benjamin Johnston
Author Profile Icon Benjamin Johnston
Benjamin Johnston
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Introduction


In the previous chapter, we began our supervised machine learning journey using regression techniques, predicting the continuous variable output given a set of input data. We will now turn to the other sub-type of machine learning problems that we previously described: classification problems. Recall that classification tasks aim to predict, given a set of input data, which one of a specified number of groups of classes data belongs to.

In this chapter, we will extend the concepts learned in Chapter 3, Regression Analysis, and will apply them to a dataset labeled with classes, rather than continuous values, as output.

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