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Models identify trends and behaviors from "summary" of Predictive Analytics by Eric Siegel
Predictive models are designed to identify patterns, trends, and behaviors within data. By analyzing historical data, these models can uncover insights that can be used to make predictions about future outcomes. This process involves identifying key variables that are likely to influence the outcome of interest and building a mathematical model that can accurately predict how these variables will interact. Models can be trained using a variety of techniques, including regression analysis, decision trees, and neural networks. Each of these methods has its own strengths and weaknesses, and the choice of technique will depend on the specific characteristics of the data being analyzed. Once a model has been trained, it can be used to make predictions about new data that it has not seen before. This process, known as scoring, involves applying the model to the new data and g...
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