Density peaks clustering (DPC) algorithm is a new algorithm based on density clustering
analysis, which can quickly obtain the cluster centers by drawing the decision diagram by …

Clustering techniques can group genes based on similarity in biological functions. However,
the drawback of using clustering techniques is the inability to identify an optimal number of …

User behavior analysis is the research foundation of power load forecasting and power
abnormal detection, and it is the theoretical support for smart grid planning and the …

Precise forecasting of survival risk plays a pivotal role in comprehending and predicting the
prognosis of patients afflicted with esophageal squamous cell carcinoma (ESCC). The …

In density peaks clustering, its complexity for computing local density and relative distance of
samples raises a scalability issue for processing large datasets. To address the issue …

Rodriguez et al. published an algorithm called clustering by fast search and find of density
peaks (DPC) in Science in June 2014. It can quickly search the density peaks and cluster …

The advancement of data mining technology presents a way to examine and analyse the
medical databases. Microarray data help in analysing the gene expressions, and the …

Breast cancer is one of the most challenging issues in the health industry today. It takes
many lives per year around the globe. It must be diagnosed at the early stages so that it can …

Cancer subty** is of great importance for the prediction, diagnosis, and precise treatment
of cancer patients. Many clustering methods have been proposed for cancer subty**. In …

Clustering is an important technology of data mining, which plays a vital role in bioscience,
social network and network analysis. As a clustering algorithm based on density and …