Methoden vergelijken

	Ethnographic Decision Modeling	Beslisboom
Vakgebied	Anthropology	Machine learning
Familie	Process / pipeline	Machine learning
Jaar van ontstaan	1989	1984
Grondlegger	Christina H. Gladwin	Breiman, Friedman, Olshen & Stone
Type	Qualitative-formal model of real-world choice behavior	Recursive partitioning (if-then rules)
Oorspronkelijke bron	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.
Aliassen	Ethnographic Decision Tree Modeling, EDTM, Decision Tree Ethnography, Ethnographic Decision Models	Karar Ağacı (Decision Tree), karar ağacı, classification tree, regression tree
Verwant	2	5
Samenvatting	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.