# R^{2}

R^{2} measures how well a regression model fits the actual data. In other words,
it is a measure of the overall accuracy of the model. R squared is also known as the coefficient of
determination.

In IBM® Cognos Analytics, R^{2} is used to
measure the accuracy of a CHAID regression tree.

R^{2} is measured on a scale of 0 to 1. A value of 1 indicates
a model that perfectly predicts values in the target field. A value
of 0 indicates a model that has no predictive value. In the real world,
R^{2} lies between these values.

When there is only one input, R squared is same as the Pearson correlation square.