Linear Regression and Optimization Techniques question

lasso
linear_regression
regularization
ridge_regression
stochastic

#1

Hello,

I am taking a general scenario using a Linear regression model

Once we have trained and predicted a Linear regression model the next step is to improve its performance by way of optimization for example using :

  • Ridge Regression

  • Lasso Regression

Now my questions are as follows :

  • Ridge and Lasso are these also “Linear Regression” models which use L2 and L1 optimization techniques. Please clarify

  • Can Ridge and Lasso be applied to any other algorithm besides Linear Regression

  • Do we GridsearchCV and RandomSearchCV to automate the process hyper-parameter tuning in the algorithms…say in the above case to set the values of Alpha.

  • When do we use GradientDescent especially Stochastic Gradient Descent…can we also use SGD classifier along with Linear Regression, Ridge and Lasso

Thanks

Mohit