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Exercise

Logistic regression with glm()

Linear regression and logistic regression are special cases of a broader type of models called generalized linear models ("GLMs"). A linear regression makes the assumption that the residuals follow a Gaussian (normal) distribution. By contrast, a logistic regression assumes that residuals follow a binomial distribution.

Here, you'll model how the length of relationship with a customer affects churn.

churn is available.

Instructions

100 XP
  • Fit a logistic regression of has_churned versus time_since_first_purchase using the churn dataset. Assign to mdl_churn_vs_relationship.