Dears, I am new in applying machine learning models. I am confused about the steps that should be applied to know exactly the type of regression model that should be used for my dataset. I read a lot and am confused now.
Should I follow the following?
1- Visualize the data
2- If it has a linear pattern, apply linear regression. If not, should I apply the non-linear model?
OR
Should I apply the linear model directly because it is easier to interpret? and it is okay to apply the linear model on non-linear datasets as shown here in this link:
Note: I want to find the correlation between 1 continuous dependent variable and multiple continuous independent variables
I hope to help me with that
You will need to provide more detail about your dataset.