Linear regression (Link opens in a new window) (also known as ordinary least squares regression, or OLS) is best used when there are one or more predictors that have a linear relationship between the prediction and the prediction target, they aren't affected by the same underlying conditions, and they don't represent two instances of the same data (for example, sales expressed in both dollars and euros). These models support different use cases and prediction types, as well as have different limitations. If the predictions were close, the trendline will start where x and y axes meet and will be in a 45 degree angle.Predictive modeling functions support linear regression, regularized linear regression, and Gaussian process regression. You’ll see a straight line passing through all the data points.
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