Linear Regression Model. Table for input and response data. Choose a model or range of models.
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Regression models are used to describe relationships between variables by fitting a line to the observed data. Numeric matrix for input data numeric vector for response. The relationship can be established with the help of fitting a best line.
Regression models are used to describe relationships between variables by fitting a line to the observed data.
Dataset array for input and response data. The factors that are used to predict the value of the dependent variable are called the independent variables. Linear regression is a type of machine learning algorithm that is used to model the relation between scalar dependent and one or more independent variables. Parameters fit intercept bool default true.
