ScholarGate
Asistent

Usporedite metode

Pregledajte odabrane metode jednu uz drugu; retci koji se razlikuju su istaknuti.

Stablo odlučivanja×Logistička regresija×
PodručjeStrojno učenjeIstraživačka statistika
ObiteljMachine learningProcess / pipeline
Godina nastanka19841958
TvoracBreiman, Friedman, Olshen & StoneDavid Roxbee Cox
VrstaRecursive partitioning (if-then rules)Method
Temeljni izvorBreiman, L., Friedman, J.H., Olshen, R.A. & Stone, C.J. (1984). Classification and Regression Trees. Wadsworth. DOI ↗Cox, D. R. (1958). The regression analysis of binary sequences. Journal of the Royal Statistical Society, Series B, 20(2), 215–242. DOI ↗
Drugi naziviKarar Ağacı (Decision Tree), karar ağacı, classification tree, regression treelogit model, binomial logistic regression, LR
Srodne53
SažetakA 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.Logistic regression is a statistical method for modeling the probability of a binary outcome (disease present/absent, success/failure) as a function of continuous and categorical predictors. Developed by David Roxbee Cox (1958), it solves the problem of predicting categorical outcomes by applying a logistic transformation to constrain predictions to the [0,1] probability interval, enabling accurate risk stratification, diagnostic prediction, and causal inference in epidemiology, medicine, and social science.
ScholarGateSkup podataka
  1. v1
  2. 1 Izvori
  3. PUBLISHED
  1. v1
  2. 2 Izvori
  3. PUBLISHED

Idi na pretraživanje Preuzmi prezentaciju

ScholarGateUsporedite metode: Decision Tree · Logistic Regression. Preuzeto 2026-06-17 s https://scholargate.app/hr/compare