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Machine Learning for Data Mining

You're reading from   Machine Learning for Data Mining Improve your data mining capabilities with advanced predictive modeling

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Product type Paperback
Published in Apr 2019
Publisher Packt
ISBN-13 9781838828974
Length 252 pages
Edition 1st Edition
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Author (1):
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Jesus Salcedo Jesus Salcedo
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Jesus Salcedo
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Using graphs to interpret machine learning models

In this section, we're going to see how to use graphs to interpret the results of a machine learning model. Specifically, it's important to know what kind of data you have, because the type of data will determine the type of graph that you can create. This graph will then help you understand what goes into the predictions of a machine learning model. We will also understand how a machine learning model uses these different variables for the predictions and eventually use these predictions for our final interpretation.

For example, when we have an outcome variable that is a categorical variable and our predictor is also a categorical variable, we can use a bar chart or a web plot. We can use either type of graph to help us understand how the machine learning model is making its predictions. The following table represents...

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