Cluster-weighted modeling

Cluster-weighted modeling is a type of machine learning technique which is used to predict how a group of people will behave. It looks at the characteristics of a group of people and then finds patterns in the data which can be used to predict how all the people in the group will behave. For example, if you were trying to predict how all the people in a city will vote in an upcoming election, you could use cluster-weighted modeling to look at the characteristics of each person (age, gender, political affiliation, etc.), and find patterns in the data which might indicate how the entire population will vote.