পদ্ধতির তুলনা করুন

	ডিবিস্ক্যান	ব্যাখ্যামূলক কে-নিয়ারেস্ট নেইবারস
ক্ষেত্র	যন্ত্র শিখন	যন্ত্র শিখন
পরিবার	Machine learning	Machine learning
উদ্ভবের বছর	1996	1967 (KNN); 2010s (explainability extensions)
প্রবর্তক	Ester, M., Kriegel, H.-P., Sander, J. & Xu, X.	Cover, T. & Hart, P. (KNN); XAI extensions by various authors
ধরন	Density-based clustering algorithm	Instance-based learning with explainability layer
মৌলিক উৎস	Ester, M., Kriegel, H.-P., Sander, J. & Xu, X. (1996). A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise. Proceedings of the 2nd KDD, 226–231.	Cover, T. & Hart, P. (1967). Nearest neighbor pattern classification. IEEE Transactions on Information Theory, 13(1), 21–27.
অপর নাম	DBSCAN Kümeleme, density-based clustering, density-based spatial clustering	XKNN, Interpretable KNN, Explainable KNN, Transparent K-Nearest Neighbors
সম্পর্কিত	3	4
সারসংক্ষেপ	DBSCAN is a density-based clustering algorithm, introduced by Ester, Kriegel, Sander and Xu in 1996, that groups together points lying in dense regions and flags points in sparse regions as noise. It is effective on noisy data and on clusters of irregular, non-spherical shapes.	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.