Name
Abstract | ||
|---|---|---|
This paper analyses the advantages and disadvantages of the K-means algorithm and the DENCLUE algorithm. In order to realise the automation of clustering analysis and eliminate human factors, both partitioning and density-based methods were adopted, resulting in a new algorithm – Clustering Algorithm based on object Density and Direction (CADD). This paper discusses the theory and algorithm design of the CADD algorithm. As an illustration of its applicability, CADD was used to cluster real world data from the geochemistry domain. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/CIMCA.2008.34 | computational intelligence |
Keywords | Field | DocType |
density-based method,geochemistry domain,cadd algorithm,clustering algorithm incorporating density,clustering analysis,algorithm design,new algorithm,k-means algorithm,clustering algorithm,denclue algorithm,cluster real world data,cluster analysis,data mining,human factors,set theory,k means algorithm,algorithms,clustering algorithms,noise,algorithm design and analysis,data structures | k-means clustering,Data mining,Canopy clustering algorithm,CURE data clustering algorithm,Algorithm design,Computer science,Computer Aided Design,FSA-Red Algorithm,Artificial intelligence,k-medoids,Cluster analysis,Machine learning | Conference |
Citations | PageRank | References |
0 | 0.34 | 5 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuchen Song | 1 | 4 | 3.33 |
| M.J. O’Grady | 2 | 209 | 19.33 |
| Gregory M. P. O'Hare | 3 | 977 | 103.51 |
| Wei Wang | 4 | 0 | 0.68 |