An Introduction to Ridge, Lasso, and Elastic Net #regression
▻https://hackernoon.com/an-introduction-to-ridge-lasso-and-elastic-net-regression-cca60b4b934f?s
A guide to Ridge, Lasso, and Elastic Net Regression and applying it in RRegression analysis is a statistical technique that models and approximates the relationship between a dependent and one or more independent variables. This article will quickly introduce three commonly used regression models using #r and the Boston housing data-set: Ridge, Lasso, and Elastic Net.First we need to understand the basics of regression and what parameters of the equation are changed when using a specific model. Simple linear regression, also known as ordinary least squares (OLS) attempts to minimize the sum of error squared. The error in this case is the difference between the actual data point and its predicted value.Visualization of the squared error (from Setosa.io)The equation for this model is (...)