| 000 | 03288nam a22004695i 4500 | ||
|---|---|---|---|
| 999 |
_c368376 _d368376 _x1 |
||
| 001 | 368376 | ||
| 003 | ES-MaUEC | ||
| 005 | 20230102121729.0 | ||
| 006 | a||||fo|||| 00| 0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 220402s2022 sz | s |||| 0|eng d | ||
| 020 | _a9783030940669 | ||
| 024 | 7 |
_a10.1007/978-3-030-94066-9 _2doi |
|
| 040 |
_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC |
||
| 050 | 4 |
_aQA248.5 _b2022 EB |
|
| 100 | 1 |
_aEftekhari, Mahdi _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9683354 |
|
| 245 | 1 | 0 |
_aHow Fuzzy Concepts Contribute to Machine Learning _cby Mahdi Eftekhari, Adel Mehrpooya, Farid Saberi-Movahed, Vicenç Torra |
| 250 | _aFirst edition 2022 | ||
| 264 | 1 |
_aCham _bSpringer International Publishing _c2022 |
|
| 300 |
_a1 recurso en línea (XII, 167 páginas) _b41 ilustraciones a color |
||
| 336 |
_2rdacontent _aTexto _btxt |
||
| 337 |
_2rdamedia _aelectrónico _bc |
||
| 338 |
_2rdacarrier _arecurso electrónico _bcr |
||
| 347 |
_aarchivo de texto _bPDF |
||
| 490 | 0 |
_aStudies in Fuzziness and Soft Computing _x1860-0808 _v416 |
|
| 505 | 0 | _aChapter 1: Preliminaries -- Chapter 2: A Definition for Hesitant Fuzzy Partitions -- Chapter 3: Unsupervised Feature Selection Method. Chapter 4: Fuzzy Partitioning of Continuous Attributes -- Chapter 5: Comparing Different Stopping Criteria. | |
| 520 | _aThis book introduces some contemporary approaches on the application of fuzzy and hesitant fuzzy sets in machine learning tasks such as classification, clustering and dimension reduction. Many situations arise in machine learning algorithms in which applying methods for uncertainty modeling and multi-criteria decision making can lead to a better understanding of algorithms behavior as well as achieving good performances. Specifically, the present book is a collection of novel viewpoints on how fuzzy and hesitant fuzzy concepts can be applied to data uncertainty modeling as well as being used to solve multi-criteria decision making challenges raised in machine learning problems. Using the multi-criteria decision making framework, the book shows how different algorithms, rather than human experts, are employed to determine membership degrees. The book is expected to bring closer the communities of pure mathematicians of fuzzy sets and data scientists. | ||
| 988 | _aSpringer_Robotics_2022 | ||
| 650 | 7 |
_2embne _9145903 _aConjuntos difusos |
|
| 650 | 7 |
_2embne _9166090 _aAprendizaje automático |
|
| 700 | 1 |
_aMehrpooya, Adel _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9683355 |
|
| 700 | 1 |
_aSaberi-Movahed, Farid _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9683356 |
|
| 700 | 1 |
_aTorra, Vicenç _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9683357 |
|
| 776 | 0 | 8 |
_iPrinted edition: _z9783030940652 |
| 776 | 0 | 8 |
_iPrinted edition: _z9783030940676 |
| 776 | 0 | 8 |
_iPrinted edition: _z9783030940683 |
| 856 | 4 | 0 |
_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-94066-9 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid) |
| 942 |
_2lcc _cLE _n0 |
||
| 998 |
_b04/2022 _dz _eIG _zSI |
||