Finding gender affinity for businesses What are the different models I can use to find the gender affinity of businesses using yelp dataset-- https://www.kaggle.com/yelp-dataset/yelp-dataset . I need to find Probablity (Male buying from a merchant) and Probablity (Female buying from a merchant) where both probablities add to 1 . There is no information about gender so I can use the Genderize api to find gender using names of users. This is an unsupervised problem
Since you're only interested in the gender affinity of businesses in your dataset, no model is needed.  You can compute gender affinity directly:  For each business, find the total number of customers, the total number of male customers, and the total number of female customers.  Then $Pr(Male) = \frac{males}{total}$ and $Pr(Female) = \frac{females}{total}$