A Clustering-based Method for Business Hall Efficiency Analysis

Algorithm 1

LSH-based -means.

Required: Training dataset ; the size of dataset ; the minimum number of data points in one cluster; the maximum distance in one cluster ; the closest set , where and is a two-dimensional array; is the number of clusters.
Output: The final clustering result.
(1)	Initialize LSH.
(2)	Index dataset via LSH.
(3)	Let .
(4)	Let .//copy
(5)	whiledo
(6)	.
(7)	Randomly select one point from dataset .
(8)	.
(9)	is removed from .
(10)	= query .
(11)	Let
(12)	fordo
(13)	.
(14)	ifthen
(15)	break;
(16)	end if
(17)	ifthen
(18)	removed from .
(19)	.
(20)	end if
(21)	end for
(22)	end while
(23)	Compute the centeroids via .
(24)	Function
(25)	The final clustering result. .