Clustering by defining and merging candidates of cluster centers via independence and affinity
Sign Up to like & getrecommendations! Published in 2018 at "Neurocomputing"
DOI: 10.1016/j.neucom.2018.07.043
Abstract: Abstract Clustering analysis is to classify elements into categories based on their similarity. Clustering by fast search and find of density peaks (CFSFDP) has been proven to be an effective and novel algorithm, which identifies… read more here.
Keywords: clustering defining; cluster; affinity; defining merging ... See more keywords
Fast Density Clustering Algorithm for Numerical Data and Categorical Data
Sign Up to like & getrecommendations! Published in 2017 at "Mathematical Problems in Engineering"
DOI: 10.1155/2017/6393652
Abstract: Data objects with mixed numerical and categorical attributes are often dealt with in the real world. Most existing algorithms have limitations such as low clustering quality, cluster center determination difficulty, and initial parameter sensibility. A… read more here.
Keywords: density clustering; cluster centers; fast density; clustering algorithm ... See more keywords