পদ্ধতির তুলনা করুন

	ব্যাখ্যামূলক কে-নিয়ারেস্ট নেইবারস	নেইভ বেইজ
ক্ষেত্র	যন্ত্র শিখন	যন্ত্র শিখন
পরিবার	Machine learning	Machine learning
উদ্ভবের বছর	1967 (KNN); 2010s (explainability extensions)	1997
প্রবর্তক	Cover, T. & Hart, P. (KNN); XAI extensions by various authors	Mitchell, T. M. (textbook treatment)
ধরন	Instance-based learning with explainability layer	Probabilistic classifier (Bayes' theorem with conditional independence)
মৌলিক উৎস	Cover, T. & Hart, P. (1967). Nearest neighbor pattern classification. IEEE Transactions on Information Theory, 13(1), 21–27.	Mitchell, T. M. (1997). Machine Learning. McGraw-Hill. ISBN: 978-0070428072
অপর নাম	XKNN, Interpretable KNN, Explainable KNN, Transparent K-Nearest Neighbors	Naive Bayes Sınıflandırıcı, naive bayes classifier, simple Bayes, Gaussian Naive Bayes
সম্পর্কিত	4	4
সারসংক্ষেপ	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.	Naive Bayes is a fast probabilistic classifier that applies Bayes' theorem while assuming that the features are conditionally independent given the class — a method given its standard machine-learning treatment in Tom Mitchell's 1997 textbook Machine Learning. Despite this simplifying ('naive') assumption, it is quick to train and often surprisingly accurate.