Can we limit the value of a response variable in any machine learning algorithm?
It depends on the meaning of your response variable, considering you are using linear regression. But in a general function y=f(x), you can add a Softmax function y=Softmax(f(x)) to make sure y in (0, 1). If you replace Softmax with sigmoid and use it for regression, then you get a Logistic regression, they you can limit the response value to (0, 1).
I am working on a problem in which my response variable is a relative power whose value cannot go beyond 100%. When I use linear regression or any other machine-learning algorithms, the predicted value goes beyond 100% and I want to limit that to 100%. Is there any way we can achieve that?