What are the advantages and Disadvantages of Regression Algorithms
Advantages:
- Easy and simple
implementation.
- Space complex solution.
- Fast training.
- Value of θ coefficients
gives an assumption of feature significance.
Disadvantages:
- Applicable only if the
solution is linear. In many real-life scenarios, it may not be the case.
- Algorithm assumes the
input residuals (error) to be normal distributed, but may not be satisfied
always.
- Algorithm assumes input
features to be mutually-independent (no co-linearity).