Name
Abstract | ||
|---|---|---|
In light of the remarkable diversity of data, arises an interesting and challenging problem of their description and concise interpretation. In a nutshell, in the proposed description pursued in this study, we consider a framework of information granules. The study develops a general scheme composed of two functional phases: (i) clustering data and features forming segments of original data and delivering a meaningful partition of data, and (ii) development of information granules. In both phases, we discuss a suite of performance indexes quantifying the quality of segments of data and the resulting information granules. Along this line, discussed are collections of information granules and their mutual relationships. A series of publicly available data sets is used in the experiments-their granular signature is quantified, and the quality of these findings is analyzed. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1007/s40815-020-00903-z | INTERNATIONAL JOURNAL OF FUZZY SYSTEMS |
Keywords | DocType | Volume |
Information granules, Multiview perspective, Clustering, Reconstruction, Classification, Prediction, Granular signature of data | Journal | 22 |
Issue | ISSN | Citations |
6 | 1562-2479 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Abdullah Saeed Balamash | 1 | 158 | 7.99 |
| W. Pedrycz | 2 | 13966 | 1005.85 |
| Rami Al-hmouz | 3 | 323 | 19.34 |
| Ali Morfeq | 4 | 275 | 17.38 |