R includes support for a number of machine learning algorithms through the default stats package and other optional packages like glmnet, cluster etc. The machine learning algorithms typically operate directly on data frames and use C or For- tran linkages for efficient implementations. One of the most widely used machine learning functions in R is the glm method that fits Generalized Linear Models. The glm method in R lets users specify the modeling of a response variable in a compact symbolic form using formulas. For example, the formula y ∼ a + b indicates the response y is modeled linearly by variables a and b. glm also lets users specify the loss function to use and can thus be to used to implement linear regression, logistic regression etc. The glm method returns a model trained using the input data and users typically use the summary function in R to print a number of statistics com- puted about the model.
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