Krahasoni metodat

	Extra Trees i Shpjegueshëm	Pemët e vendimmarrjes
Fusha	Mësimi i makinës	Mësimi i makinës
Familja	Machine learning	Machine learning
Viti i origjinës	2006 (Extra Trees); 2017 (SHAP integration)	1984
Krijuesi	Geurts, P., Ernst, D., Wehenkel, L. (Extra Trees); Lundberg, S. M. (SHAP explainability layer)	Breiman, Friedman, Olshen & Stone
Lloji	Ensemble (randomized trees) with post-hoc explainability	Recursive partitioning (if-then rules)
Burimi themelues	Geurts, P., Ernst, D., & Wehenkel, L. (2006). Extremely randomized trees. Machine Learning, 63(1), 3–42.	Breiman, L., Friedman, J.H., Olshen, R.A. & Stone, C.J. (1984). Classification and Regression Trees. Wadsworth.
Emërtime të tjera	XAI-ET, Explainable ET, Interpretable Extra Trees, Extra Trees with SHAP	Karar Ağacı (Decision Tree), karar ağacı, classification tree, regression tree
Të lidhura	5	5
Përmbledhja	Explainable Extra Trees combines the Extremely Randomized Trees (Extra Trees) ensemble algorithm with post-hoc explainability methods — most commonly SHAP values — to deliver both strong predictive performance and transparent, feature-level explanations. It extends the classic Extra Trees classifier or regressor so that every prediction can be decomposed into individual feature contributions, satisfying demands for accountability in applied and regulated domains.	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.