Using the famous dasatest of mtcats, I provide explorations of three important supervised machine learning regressions of Lasso, Ridge, and StepLR.I'm testing which model performs the best using the training and testing data. My suggestion is that the ideal model would be Step-wise backward regression since training has an r-squared of 0.9 and testing has an r-squared of 0.857 with a relatively small measure of error.
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Using the mtcars dataset, I'm exploring three different types of regression: (1) Lasso; (2) Ridge ; (3) StepLR . I'm providing my recommendations on which one is the most ideal.
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