Classifying data with logistic regression

Logistic regression is a form of probabilistic statistical classification model, which can be used to predict class labels based on one or more features. The classification is done by using the logit function to estimate the outcome probability. One can use logistic regression by specifying the family as a binomial while using the glm function. In this recipe, we will introduce how to classify data using logistic regression.

Getting ready

You need to have completed the first recipe by generating training and testing datasets.

How to do it...

Perform the following steps to classify the churn data with logistic regression:

  1. With the specification of family as a binomial, we apply the glm function on the dataset, ...

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