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If you’ve studied a bit of statistics or machine learning, there is a good chance you have come across logistic regression (aka binary logit). It…

This post describes how to interpret the coefficients, also known as parameter estimates, from logistic regression (aka binary logit and binary logistic regression). It does…

Feature engineering refers to the process of manipulating predictor variables (features) with the goal of improving a predictive model. In this post I outline some of the…

When creating a predictive model, there are two types of predictors (features): numeric variables, such as height and weight, and categorical variables, such as occupation…

When building a predictive model, it is often practical to improve predictive performance by modifying the numeric variables in some way. In statistics, this is…

Logistic regression, also known as binary logit and binary logistic regression, is a particularly useful predictive modeling technique, beloved in both the machine learning and the statistics communities. It…