## Machine Learning.

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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…

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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…

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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…

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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…

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A Receiver Operator Characteristic (ROC) curve is a graphical plot used to show the diagnostic ability of binary classifiers. It was first used in signal…

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When using linear discriminant analysis (LDA) in market research, a common need is to obtain what are known as discriminant functions. These allow the analysis…

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In this post I show how discriminant functions can be extracted from a Linear Discriminant Analysis in Displayr. Such functions are often used in Excel…

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