Methoden vergelijken
Bekijk de geselecteerde methoden naast elkaar; rijen die verschillen zijn gemarkeerd.
| Uitlegbare K-Nearest Neighbors× | Beslisboom× | |
|---|---|---|
| Vakgebied | Machine learning | Machine learning |
| Familie | Machine learning | Machine learning |
| Jaar van ontstaan≠ | 1967 (KNN); 2010s (explainability extensions) | 1984 |
| Grondlegger≠ | Cover, T. & Hart, P. (KNN); XAI extensions by various authors | Breiman, Friedman, Olshen & Stone |
| Type≠ | Instance-based learning with explainability layer | Recursive partitioning (if-then rules) |
| Oorspronkelijke bron≠ | Cover, 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 ↗ |
| Aliassen≠ | XKNN, Interpretable KNN, Explainable KNN, Transparent K-Nearest Neighbors | Karar Ağacı (Decision Tree), karar ağacı, classification tree, regression tree |
| Verwant≠ | 4 | 5 |
| Samenvatting≠ | Explainable 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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