Selective naive Bayes predictor with mixtures of truncated exponentials
Naive Bayes models have been successfully used in classification problems where the class variable is discrete. Naive Bayes models have been applied to regression or prediction problems, i.e. classification problems with continuous class, but usually under the assumption that the joint distribution...
| Main Authors: | , , |
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| Format: | info:eu-repo/semantics/report |
| Language: | English |
| Published: |
2012
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| Online Access: | http://hdl.handle.net/10835/1547 |
| _version_ | 1789406473011331072 |
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| author | Morales, María Rodríguez, Carmelo Salmerón Cerdán, Antonio |
| author_facet | Morales, María Rodríguez, Carmelo Salmerón Cerdán, Antonio |
| author_sort | Morales, María |
| collection | DSpace |
| description | Naive Bayes models have been successfully used in classification problems where the class variable is discrete. Naive Bayes models have been applied to regression or prediction problems, i.e. classification problems with continuous class, but usually under the assumption that the joint distribution of the feature variables and the class is multivariate Gaussian. In this paper we are interested in regres- sion problems where some of the feature variables are discrete while the others are continuous. We propose a Naive Bayes predictor based on the approximation of the joint distribution by a Mixture of Truncated Exponentials (MTE). We have designed a procedure for selecting the variables that should be used in the construction of the model. This scheme is based on the mutual information between each of the candidate variables and the class. Since the mutual information can not be computed exactly for the MTE distribution, we introduce an unbiased estimator of it, based on Monte Carlo methods. We test the performance of the proposed model in three real life problems, related to higher education management. |
| format | info:eu-repo/semantics/report |
| id | oai:repositorio.ual.es:10835-1547 |
| institution | Universidad de Cuenca |
| language | English |
| publishDate | 2012 |
| record_format | dspace |
| spelling | oai:repositorio.ual.es:10835-15472023-04-12T19:40:05Z Selective naive Bayes predictor with mixtures of truncated exponentials Morales, María Rodríguez, Carmelo Salmerón Cerdán, Antonio Naive Bayes models have been successfully used in classification problems where the class variable is discrete. Naive Bayes models have been applied to regression or prediction problems, i.e. classification problems with continuous class, but usually under the assumption that the joint distribution of the feature variables and the class is multivariate Gaussian. In this paper we are interested in regres- sion problems where some of the feature variables are discrete while the others are continuous. We propose a Naive Bayes predictor based on the approximation of the joint distribution by a Mixture of Truncated Exponentials (MTE). We have designed a procedure for selecting the variables that should be used in the construction of the model. This scheme is based on the mutual information between each of the candidate variables and the class. Since the mutual information can not be computed exactly for the MTE distribution, we introduce an unbiased estimator of it, based on Monte Carlo methods. We test the performance of the proposed model in three real life problems, related to higher education management. 2012-05-28T08:38:24Z 2012-05-28T08:38:24Z 2006 info:eu-repo/semantics/report Proceedings of the ICMSM'06. http://hdl.handle.net/10835/1547 en info:eu-repo/semantics/openAccess International Conference on Mathematical and Statistical Modeling in Honor of Enrique Castillo. |
| spellingShingle | Morales, María Rodríguez, Carmelo Salmerón Cerdán, Antonio Selective naive Bayes predictor with mixtures of truncated exponentials |
| title | Selective naive Bayes predictor with mixtures of truncated exponentials |
| title_full | Selective naive Bayes predictor with mixtures of truncated exponentials |
| title_fullStr | Selective naive Bayes predictor with mixtures of truncated exponentials |
| title_full_unstemmed | Selective naive Bayes predictor with mixtures of truncated exponentials |
| title_short | Selective naive Bayes predictor with mixtures of truncated exponentials |
| title_sort | selective naive bayes predictor with mixtures of truncated exponentials |
| url | http://hdl.handle.net/10835/1547 |
| work_keys_str_mv | AT moralesmaria selectivenaivebayespredictorwithmixturesoftruncatedexponentials AT rodriguezcarmelo selectivenaivebayespredictorwithmixturesoftruncatedexponentials AT salmeroncerdanantonio selectivenaivebayespredictorwithmixturesoftruncatedexponentials |