Find suitable locations using Machine Learning
Are you sure PCA is the correct way to go?
It's an analytical problem and being able to interpret the results are very important.

How about the correlation between the number of stores and nearby features? Find out what makes a good location. What are the most important features? Run forward or backward selection as an example, or use another model/feature selection technique.

It's not a pure machine learning case you have here. It's a typical analytical data science problem.

If you still want to do classification, just train a model. You have POI features and some others. You know if there is a store or not :) I might not fully understand the problem here. You train on a 50% a store exist location, and 50% a store does not exist in this location dataset. Train a classifier, and classify other areas. 

I'd still start to visualize and understand the data as I mentioned first. It's much underrated and the way to start solving most problems.

Hope that gave you some hints,

Cheers