Table 14: Clustering and association algorithms.
Clustering Algorithms | ||
k-medoids clustering | 2 | [FS43] [FS29] |
k-means clustering | 21 | [FS32] [FS7][FS44][FS25][FS1][FS17][FS3][FS46] FS26][FS9][FS19][FS20][FS39][FS2][FS30][FS11] [FS12][FS47][FS22][FS42] [FS51] [FS56] |
Hierarchical Agglomerative Clustering Algorithm (HAC) | 20 | [FS15][FS33][FS34][FS35][FS36][FS8][FS17][FS4][FS18] [FS27][FS37][FS28][FS29][FS21][FS48][FS40] [FS51] [FS54] [FS55] [FS57] |
Density-based spatial clustering of applications with noise (DBSCAN) | 1 | [FS5] |
Quality Threshold (QT) clustering algorithm | 2 | [FS45][FS24] |
neural network clustering | 1 | [FS13] |
PSO clustering algorithm | 1 | [FS23] |
self-organizing based clustering algorithm | 1 | [FS31] |
Self-Join RDB Clustering | 1 | [FS38] |
tree-traversing ant algorithm | 1 | [FS41] |
Fuzzy C-Means | 2 | [FS50] [FS52] |
Association Rules Algorithms | ||
Hyperclique patterns | 1 | [FS33] |
Apriori algorithm | 4 | [FS16] [FS10][FS6] [FS53] |
GARC: gain based association rule classification | 1 | [FS35] |
defined correlation | 2 | [FS2][FS14] |