Lasso Regression

Lasso Regression

Lasso Regression It is similar to the ridge regression , the Lasso (Least Absolute Shrinkage and Selection Operator) it is penalizes the absolute size of regression coefficients and it reduces the variability and increase the accuracy. Lasso is mainly used when we are having the large number of features because Lasso does the feature selection. The lasso regression will give the results in sparse matrix with less coefficients and some co-efficient becomes zero.   In this we are having the feature selection It is also called as L1 regularization technique. Lets take a dataset and perform the Lasso regression ,…