If a machine learning project has a large number of attributes/features say 50+ then :
Analyzing the relationship between them one by one can be a cumbersome process and will consume a lot of time. Understanding bi-variate relationships can be more tedious and complex
One might get lost in the whole process due to the confusion & complexity created by some many attributes
So how do we manage the whole process of analyzing relationships when there are large number of features so as to have a better grip and understanding over the whole process.
Are there any best practices to share to manage the whole process?
Thanks & Regards,