ML Algorithm for getting top pick in each sample

Question

I have a dataset of streets - and each street contains several houses.

street_id | house_id | number of calls | number of people living
1         | 1        | 10              | 5
1         | 2        | 3               | 1
2         | 3        | 4               | 2
2         | 4        | 15              | 19

1. My goal is to find for each street, the most popular house.
2. I have GT - streets with several houses, and for each street, which house was the most popular house.
3. For the data example above - the results should be (street 1 -> house 1, street 2 -> house 4) because houses #1, #4 are the most popular in their street.

We can find the most popular street using features about each house -

• number of calls made from house
• number of people living in house
• etc

But we don't need to find all of the popular houses from all of the houses - we need for each street, to find the most popular house.

Do you know how can I solve this task?
I've thought about regular classification, but that would results giving all of the popular houses, and not one for each street.

Thanks in advance!