Name
Title | ||
|---|---|---|
Improving Supervised Learning Classification Methods Using Multigranular Linguistic Modeling and Fuzzy Entropy. |
Abstract | ||
|---|---|---|
Obtaining good classification results using supervised learning methods is critical if we want to obtain a high level of precision in the classification processes. The training data used for the learning process play a very important role in achieving this objective. Therefore, it is important to represent the data in a way that best expresses its meaning. For this purpose, we propose to apply lin... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/TFUZZ.2016.2594275 | IEEE Transactions on Fuzzy Systems |
Keywords | Field | DocType |
Pragmatics,Supervised learning,Computational modeling,Complexity theory,Training data,Entropy,Data models | Data modeling,Semi-supervised learning,Pragmatics,Expression (mathematics),Computer science,Supervised learning,Readability,Granular computing,Artificial intelligence,Granularity,Linguistics,Machine learning | Journal |
Volume | Issue | ISSN |
25 | 5 | 1063-6706 |
Citations | PageRank | References |
20 | 0.81 | 24 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Juan Antonio Morente-Molinera | 1 | 162 | 16.00 |
| József Mezei | 2 | 202 | 20.07 |
| Christer Carlsson | 3 | 1844 | 164.70 |
| Enrique Herrera-Viedma | 4 | 13105 | 642.24 |