Predicting Facial Biotypes Using Continuous Bayesian Network Classifiers
Bayesian networks are useful machine learning techniques that are able to combine quantitative modeling, through probability theory, with qualitative modeling, through graph theory for visualization. We apply Bayesian network classifiers to the facial biotype classification problem, an important sta...
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| Format: | Article |
| Language: | English |
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Wiley
2018-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2018/4075656 |
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| author | Gonzalo A. Ruz Pamela Araya-Díaz |
| author_facet | Gonzalo A. Ruz Pamela Araya-Díaz |
| author_sort | Gonzalo A. Ruz |
| collection | DOAJ |
| description | Bayesian networks are useful machine learning techniques that are able to combine quantitative modeling, through probability theory, with qualitative modeling, through graph theory for visualization. We apply Bayesian network classifiers to the facial biotype classification problem, an important stage during orthodontic treatment planning. For this, we present adaptations of classical Bayesian networks classifiers to handle continuous attributes; also, we propose an incremental tree construction procedure for tree like Bayesian network classifiers. We evaluate the performance of the proposed adaptations and compare them with other continuous Bayesian network classifiers approaches as well as support vector machines. The results under the classification performance measures, accuracy and kappa, showed the effectiveness of the continuous Bayesian network classifiers, especially for the case when a reduced number of attributes were used. Additionally, the resulting networks allowed visualizing the probability relations amongst the attributes under this classification problem, a useful tool for decision-making for orthodontists. |
| format | Article |
| id | doaj-art-6bc71c1885a04dbaa033937deae67abd |
| institution | OA Journals |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-6bc71c1885a04dbaa033937deae67abd2025-08-20T02:06:08ZengWileyComplexity1076-27871099-05262018-01-01201810.1155/2018/40756564075656Predicting Facial Biotypes Using Continuous Bayesian Network ClassifiersGonzalo A. Ruz0Pamela Araya-Díaz1Facultad de Ingeniería y Ciencias, Universidad Adolfo Ibáñez, Av. Diagonal Las Torres 2640, Peñalolén, Santiago, ChileDepartamento del Niño y Adolescente, Área de Ortodoncia, Facultad de Odontología, Universidad Andrés Bello, Santiago, ChileBayesian networks are useful machine learning techniques that are able to combine quantitative modeling, through probability theory, with qualitative modeling, through graph theory for visualization. We apply Bayesian network classifiers to the facial biotype classification problem, an important stage during orthodontic treatment planning. For this, we present adaptations of classical Bayesian networks classifiers to handle continuous attributes; also, we propose an incremental tree construction procedure for tree like Bayesian network classifiers. We evaluate the performance of the proposed adaptations and compare them with other continuous Bayesian network classifiers approaches as well as support vector machines. The results under the classification performance measures, accuracy and kappa, showed the effectiveness of the continuous Bayesian network classifiers, especially for the case when a reduced number of attributes were used. Additionally, the resulting networks allowed visualizing the probability relations amongst the attributes under this classification problem, a useful tool for decision-making for orthodontists.http://dx.doi.org/10.1155/2018/4075656 |
| spellingShingle | Gonzalo A. Ruz Pamela Araya-Díaz Predicting Facial Biotypes Using Continuous Bayesian Network Classifiers Complexity |
| title | Predicting Facial Biotypes Using Continuous Bayesian Network Classifiers |
| title_full | Predicting Facial Biotypes Using Continuous Bayesian Network Classifiers |
| title_fullStr | Predicting Facial Biotypes Using Continuous Bayesian Network Classifiers |
| title_full_unstemmed | Predicting Facial Biotypes Using Continuous Bayesian Network Classifiers |
| title_short | Predicting Facial Biotypes Using Continuous Bayesian Network Classifiers |
| title_sort | predicting facial biotypes using continuous bayesian network classifiers |
| url | http://dx.doi.org/10.1155/2018/4075656 |
| work_keys_str_mv | AT gonzaloaruz predictingfacialbiotypesusingcontinuousbayesiannetworkclassifiers AT pamelaarayadiaz predictingfacialbiotypesusingcontinuousbayesiannetworkclassifiers |