From the course: Machine Learning with Python: Logistic Regression

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Interpreting the coefficients of logistic regression

Interpreting the coefficients of logistic regression - Python Tutorial

From the course: Machine Learning with Python: Logistic Regression

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Interpreting the coefficients of logistic regression

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- [Instructor] Logistic regression is most often used to solve classification problems because that allows us to predict the probability of a categorical value Y for a given X. However, instead of simply predicting an outcome, we sometimes want to understand the quantitative impact that a unit change in X has on Y. This is known as inference. To infer meaning from a model, we need to understand what a beta coefficients mean. The way we interpret the beta coefficients depends on whether a predictor X is continuous like age or categorical like gender. Let's start with this scenario where the predictor is continuous. The equation for such a model is shown here. Because the predictor age is a continuous variable, we interpret the beta zero coefficient of -5.95 as a log odds of a customer of age zero renting an e-bike. To understand the intuition behind this interpretation, simply substitute the value zero for age in the…

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