Name
Abstract | ||
|---|---|---|
This paper focuses on the introduction of a new evolutionary algorithm for data clustering, the Self-sizing Genome Genetic Algorithm. It is akin to a messy Genetic Algorithm and does not use a priori information about the number of clusters. A new recombination operator, gene-pooling, is introduced, while fitness is based on simultaneously maximizing intra-cluster homogeneity and inter-cluster separability. This algorithm is applied to clustering in dermatological semeiotics. Moreover, a Pathology Addressing Index is defined to quantify utility of found clusters in unambiguously addressing towards pathologies. Comparison with other clustering tools is performed. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1145/1066677.1066890 | SAC |
Keywords | Field | DocType |
new evolutionary algorithm,messy genetic algorithm,new variable,new recombination operator,self-sizing genome genetic algorithm,length genome genetic algorithm,intra-cluster homogeneity,dermatological semeiotics,inter-cluster separability,clustering tool,clustering,genetic algorithms,evolutionary algorithm,genetic algorithm,indexation,data clustering | Data mining,Canopy clustering algorithm,Fuzzy clustering,Clustering high-dimensional data,CURE data clustering algorithm,Correlation clustering,Computer science,Determining the number of clusters in a data set,FLAME clustering,Cluster analysis | Conference |
ISBN | Citations | PageRank |
1-58113-964-0 | 1 | 0.36 |
References | Authors | |
6 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| I De Falco | 1 | 314 | 16.62 |
| Ernesto Tarantino | 2 | 361 | 42.45 |
| A. Delia Cioppa | 3 | 12 | 0.91 |
| Francesco Fontanella | 4 | 58 | 15.48 |