A Clustering Algorithm via Density Perception and Hierarchical Aggregation Based on Urban Multimodal Big Data for Identifying and Analyzing Categories of Poverty-Stricken Households in China
Algorithm 1
The aggregation of neighbor clusters.
(1)
Input: clusters after initial division ; the threshold ;
(2)
Output: final clusters after aggregation
(3)
(4)
While True
(5)
Calculate by the averaged of density differences between clusters
(6)
For each cluster in
(7)
For each cluster in
(8)
Calculate
(9)
Calculate by the averaged densities for samples in the clusters
