Figure 4From: Learning to cluster urban areas: two competitive approaches and an empirical validationDropout calibration. Low dropout values (0.0 or 0.1) do not allow distinguishing the local structures of the clusters, mixing them throughout various areas of the region. However, as the dropout increases to 0.2 and 0.3, the clusters become more distinguishableBack to article page