Form follows Function
Architects and planners have always assumed that there is a relationship between form and function. This work is investigating if the function of a building can be predicted based on its geometrical attributes by using supervised machine learning techniques. Supervised learning consists in learning the link between two datasets: the observed data X and an external variable y that we are trying to predict, usually called “target” or “labels”. Have a look at the Python code and the results on my Github account here.