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 2
The proposed cluster method.
(1)
Input: parameter , clusters after initial division ; the threshold ;
(2)
Output: final clusters
(3)
(4)
While True
(5)
Calculate the local density
(6)
Select an unlabeled sample from the sequence
(7)
For.
(8)
Calculate the adaptive neighborhood radius
(9)
Select a core point from the sequence
(10)
Calculate the set of neighbor samples
(11)
For
(12)
The expansion of the -th cluster is completed
(13)
End For
(17)
End For
(18)
Calculate by the averaged of density differences between clusters
