Methoden vergleichen

	Cultural Consensus Model	Entscheidungsbaum
Fachgebiet	Anthropology	Maschinelles Lernen
Familie	Latent structure	Machine learning
Entstehungsjahr	1986	1984
Urheber	A. Kimball Romney, Susan C. Weller & William H. Batchelder	Breiman, Friedman, Olshen & Stone
Typ	Latent-structure measurement model for shared cultural knowledge	Recursive partitioning (if-then rules)
Wegweisende Quelle	Romney, A. K., Weller, S. C., & Batchelder, W. H. (1986). Culture as consensus: A theory of culture and informant accuracy. American Anthropologist, 88(2), 313–338.	Breiman, L., Friedman, J.H., Olshen, R.A. & Stone, C.J. (1984). Classification and Regression Trees. Wadsworth.
Aliasnamen	Cultural Consensus Theory, CCT, Consensus Analysis, Informant Accuracy Model	Karar Ağacı (Decision Tree), karar ağacı, classification tree, regression tree
Verwandt	4	5
Zusammenfassung	The cultural consensus model is a latent-structure measurement framework that estimates the culturally shared answers to a set of questions and, simultaneously, how much each informant knows, without the researcher knowing the correct answers in advance. Introduced by Romney, Weller and Batchelder in 1986, it treats agreement among informants as evidence of shared knowledge and uses a factor-analytic (or, in modern variants, Bayesian) decomposition to recover both a single 'answer key' and an informant-specific competence score.	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.