Please Explain the statement below :
It is least appropriate because with LASSO, when λ = 0 the penalty (i.e., regularization) term reduces to zero, so there is no regularization and the regression is equivalent to an ordinary least squares (OLS) regression.
If Possible please explain with numerical Example ?
The image attached shows the formula of Lasso regression. The only way in which the same is different from a regular regression formula is by the penalty term. If Lambda is 0, the penalty term in itself is 0. Thereby, the formula left is that of a normal OLS regression.