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Clustering by fast search and find of density peaks (CFSFDP) is proposed to cluster the data by finding of density peaks. CFSFDP is based on two assumptions that: a cluster center is a high dense data point as compared to its surrounding neighbors, and it lies at a large distance from other cluster centers. Based on these assumptions, CFSFDP supports a(More)
Clustering by fast search and find of density peaks (DP) is a method in which density peaks are used to select the number of cluster centers. The DP has two input parameters: 1) the cutoff distance and 2) cluster centers. Also in DP, different methods are used to measure the density of underlying datasets. To overcome the limitations of DP, an Adaptive-DP(More)
OBJECTIVE To determine the associations between maternal ethnicity and outcomes of infants born between 22 and 31 weeks' gestation and admitted to neonatal intensive care units in New South Wales and the Australian Capital Territory, Australia, between 1995 and 2006. DESIGN AND PATIENTS De-identified perinatal and neonatal outcome data for 10 267 infants(More)
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