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| Ethnographic Decision Modeling× | Arbre de décision× | |
|---|---|---|
| Domaine≠ | Anthropology | Apprentissage automatique |
| Famille≠ | Process / pipeline | Machine learning |
| Année d'origine≠ | 1989 | 1984 |
| Auteur d'origine≠ | Christina H. Gladwin | Breiman, Friedman, Olshen & Stone |
| Type≠ | Qualitative-formal model of real-world choice behavior | Recursive partitioning (if-then rules) |
| Source fondatrice≠ | Gladwin, C. H. (1989). Ethnographic Decision Tree Modeling. Qualitative Research Methods Series 19. Newbury Park, CA: Sage. ISBN: 9780803934870 | Breiman, L., Friedman, J.H., Olshen, R.A. & Stone, C.J. (1984). Classification and Regression Trees. Wadsworth. DOI ↗ |
| Alias≠ | Ethnographic Decision Tree Modeling, EDTM, Decision Tree Ethnography, Ethnographic Decision Models | Karar Ağacı (Decision Tree), karar ağacı, classification tree, regression tree |
| Apparentées≠ | 2 | 5 |
| Résumé≠ | Ethnographic decision tree modeling is a method for building a formal, qualitative model of how people actually make a specific recurring decision — such as whether to plant a crop, seek treatment, or adopt a practice. Developed by Christina Gladwin and set out in her 1989 Sage monograph, it elicits the criteria and rules people use through ethnographic interviews, represents them as an if-then decision tree, and then tests the tree's ability to predict the choices of a fresh sample of decision-makers. | A Decision Tree is an interpretable classification and regression method, formalised by Breiman, Friedman, Olshen and Stone in their 1984 CART framework, that partitions the data with hierarchical if-then rules. Each split sends observations down one branch or another until a prediction is read off the leaf. |
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