When the numeric output variable is estimated as a weighted sum of several input variables, the model is called
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The “effect” is often identified as “coefficient”, “weight” or “parameter”, and more simply, we say that Linear Regression computes a weighted sum of the input features, plus a constant called “bias term” or intercept [5]. To simplify, let's start with the application of the Linear Regression with one variable.
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