From the course: Machine Learning with Logistic Regression in Excel, R, and Power BI
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Calculating correlations
From the course: Machine Learning with Logistic Regression in Excel, R, and Power BI
Calculating correlations
- [Instructor] As we add different independent variable fields to logistic regression model. We want to start thinking about whether or not the field should go into the model. We can apply various statistical tests on the overall outcomes of the model, but we want to determine if there are fields we should remove because they are too closely correlated to one another. One way to determine this is by calculating the correlation between various fields in the model. You've likely heard of correlation before in statistics courses, we want to remove the inputs for the model that are closely correlated to each other, because this would cause multicollinearity between the inputs if we left the in. Think of correlation along a two-dimensional scatterplot and the points most closely in line up with the linear line, there's a strong correlation between the data points. We see a correlation of one in this example. If there isn't a…
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