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Linear regression

Ian Witten shows how to use "linear regression" to predict numeric classes, and also illustrates a method that builds trees of linear models.

Classification involves a nominal class value, whereas regression involves a numeric class. Linear regression is a classical statistical method that computes the coefficients or “weights” of a linear expression, and the predicted (“class”) value is the sum of each attribute value multiplied by its weight. A model tree is a tree where each leaf is a linear regression model; it’s like a patchwork of linear models. Linear regression and model trees are both easy to do in Weka.

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Data Mining with Weka

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