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Linear Regression Tool

The Linear Regression tool constructs a linear function to create a model that predicts a target variable based on one or more predictor variables. There are two main types of linear regression: non-regularized and regularized. Non-regularized linear regression produces linear models that minimize the sum of squared errors between the actual and predicted values of the training data target variable. Regularized linear regression balances the same minimization of sum of squared errors with a penalty term on the size of the coefficients and tends to produce simpler models less prone to overfitting. See Linear Regression.

This tool uses the R programming language. Go to Options > Download Predictive Tools to install R and the packages used by the R Tool.