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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 statistics to interpret machine learning models

In this section, we will be using statistics to interpret the results of a machine learning model. We talked about graphs and how they allow us to see and interpret the predictions of a machine learning model, but we can also use those graph for statistical tests. Have a look at the following table:

Categorical Continuous
Categorical Chi-square ANOVA
Continuous ANOVA Correlation

Let's say we had a categorical outcome variable and we had a categorical predictor, we could use the chi-square test. The chi-square test of Independence will allow us to look at the relationship between two categorical variables.

Also, if we have a categorical outcome variable and a continuous predictor, we can use ANOVA to analyze the variance. If we have two categories that we're comparing, we can have a t-test instead, which...

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