| dc.creator | Sulla-Torres, José | |
| dc.creator | Incalla Nina, Christian | |
| dc.creator | Rivera-Portugal, Margot | |
| dc.creator | Cossio-Bolaños, Marco Antonio | |
| dc.creator | Gómez-Campos, Rossana | |
| dc.date | 2023-03-29T12:25:03Z | |
| dc.date | 2023-03-29T12:25:03Z | |
| dc.date | 2019 | |
| dc.date.accessioned | 2024-05-02T20:30:48Z | |
| dc.date.available | 2024-05-02T20:30:48Z | |
| dc.identifier | http://repositorio.ucm.cl/handle/ucm/4578 | |
| dc.identifier.uri | https://repositorioslatinoamericanos.uchile.cl/handle/2250/9274820 | |
| dc.description | Low bone mineral density can lead to weak and fragile bones that lead to problems of osteoporosis and fractures in people, early detection can help their treatment. This research compares five data mining algorithms to predict bone weakness in students between 5 and 18 years of age. The methodology used for data processing is CRISP-DM. The accuracy of the algorithms applied in the referenced works with the results obtained with the WEKA data mining tool is discussed. After making the comparison, it was determined that the JRip algorithm was more precise. | |
| dc.language | en | |
| dc.rights | Atribución-NoComercial-SinDerivadas 3.0 Chile | |
| dc.rights | http://creativecommons.org/licenses/by-nc-nd/3.0/cl/ | |
| dc.source | International Conference on Inclusive Technologies and Education (CONTIE), San Jose del Cabo, Mexico, 56-566 | |
| dc.subject | Bone mineral density | |
| dc.subject | Anthropometry | |
| dc.subject | Data mining | |
| dc.subject | Rules-Jrip | |
| dc.subject | Tree-J48 | |
| dc.subject | Ramdom-tree | |
| dc.title | Comparison of classification algorithms for the detection of bone weakness in students using anthropometric data | |
| dc.type | Article | |
