It is a parametric method in reinforcement learning (RL). Supervised learning problems can be further grouped into Regression and Classification problems. Both problems have worked on the construction of a perfect model that can predict the value of the dependent attribute from the attribute variables.
In supervised learning we have more unstructured data (meaningless, missing value, unknown data) and we apply our algorithms on that and get results or conclusion.
Type of Regression :
1. Simple
- Linear
- Non Linear
2. Multiple
- Linear
- Non Linear
Liked By
Write Answer
Regression
Join MindStick Community
You have need login or register for voting of answers or question.
Prakash nidhi Verma
26-Jun-2018Regression in ML:
It is a parametric method in reinforcement learning (RL). Supervised learning problems can be further grouped into Regression and Classification problems. Both problems have worked on the construction of a perfect model that can predict the value of the dependent attribute from the attribute variables.
In supervised learning we have more unstructured data (meaningless, missing value, unknown data) and we apply our algorithms on that and get results or conclusion.
Type of Regression :
1. Simple
- Linear
- Non Linear
2. Multiple
- Linear
- Non Linear