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).