ML Algorithm for getting top pick in each sample
You will have to restructure your data in such a way that one input contains data pertaining to only one street (but of all the houses.) This involves grouping the data by street_id.
You should then use several inputs in such a way to train your model to find out the popular house. Since it will be a supervised-learning task, you'll have to label your data accordingly.
But there's a problem here. Each street has different number of houses. One way to handle this problem is by fixing an upper bound on the number of houses per street and padding your data up to this upper bound.