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Probability Density Functions
This document provides an overview of probability densities in data mining. It begins by explaining why understanding probability densities is important for working with real-valued data in data mining applications. It then covers basic notation and properties of continuous probability density functions (PDFs), including their meaning and how to calculate probabilities. It also discusses multivariate continuous PDFs, expectations, variance, standard deviation, and independence between random variables. The overall summary is that the document serves as an introduction to probability densities and their applications in data mining.
