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Vecinos más Cercanos Explicables (Explainable K-Nearest Neighbors)×Árbol de Decisión×
CampoAprendizaje automáticoAprendizaje automático
FamiliaMachine learningMachine learning
Año de origen1967 (KNN); 2010s (explainability extensions)1984
Autor originalCover, T. & Hart, P. (KNN); XAI extensions by various authorsBreiman, Friedman, Olshen & Stone
TipoInstance-based learning with explainability layerRecursive partitioning (if-then rules)
Fuente seminalCover, T. & Hart, P. (1967). Nearest neighbor pattern classification. IEEE Transactions on Information Theory, 13(1), 21–27. DOI ↗Breiman, L., Friedman, J.H., Olshen, R.A. & Stone, C.J. (1984). Classification and Regression Trees. Wadsworth. DOI ↗
AliasXKNN, Interpretable KNN, Explainable KNN, Transparent K-Nearest NeighborsKarar Ağacı (Decision Tree), karar ağacı, classification tree, regression tree
Relacionados45
ResumenExplainable K-Nearest Neighbors (XKNN) augments the classic KNN classifier or regressor with structured post-hoc or built-in explanation mechanisms, exposing which retrieved neighbors, which features, and which distance contributions drive each individual prediction — making the model's reasoning transparent and auditable for human 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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ScholarGateComparar métodos: Explainable K-Nearest Neighbors · Decision Tree. Recuperado el 2026-06-18 de https://scholargate.app/es/compare