Una alternativa al Algoritmo Chaid de segmentación basada en entropía
שמור ב:
| Autores: | , , , , |
|---|---|
| פורמט: | artículo original |
| סטטוס: | Versión publicada |
| Fecha de Publicación: | 2010 |
| תיאור: | The CHAID (Chi-Squared Automatic Interaction Detection) treebased segmentation technique has been found to be an effective approach for obtaining meaningful segments that are predictive of a K-category (nominal or ordinal) criterion variable. CHAID was designed to detect, in an automatic way, the nteraction between several categorical or ordinal predictors in explaining a categorical response, but, this may not be true when Simpson’s paradox is present. This is due to the fact that CHAID is a forward selection algorithm based on the marginal counts. In this paper we propose a backwards elimination algorithm that starts with the full set of predictors (or full tree) and eliminates predictors progressively. The elimination procedure is based on Conditional Independence contrasts using the concept of entropy. The proposed procedure is compared to CHAID. |
| País: | Portal de Revistas UCR |
| מוסד: | Universidad de Costa Rica |
| Repositorio: | Portal de Revistas UCR |
| שפה: | Español |
| OAI Identifier: | oai:archivo.portal.ucr.ac.cr:article/2127 |
| גישה מקוונת: | https://archivo.revistas.ucr.ac.cr/index.php/matematica/article/view/2127 |
| מילת מפתח: | Segmentation CHAID entropy conditional independence Segmentación entropía independencia condicional |