What Is L1 Norm?

L1 Norm is the sum of the magnitudes of the vectors in a space. It is the most natural way of measure distance between vectors, that is the sum of absolute difference of the components of the vectors. In this norm, all the components of the vector are weighted equally.

What is the difference between L1 and L2 norms?

The L1 norm that is calculated as the sum of the absolute values of the vector. The L2 norm that is calculated as the square root of the sum of the squared vector values.

What is L1 norm in Lasso?

L1 regularization: It adds an L1 penalty that is equal to the absolute value of the magnitude of coefficient, or simply restricting the size of coefficients. For example, Lasso regression implements this method. L2 Regularization: It adds an L2 penalty which is equal to the square of the magnitude of coefficients.