Krahasoni metodat

	DBSCAN	Mësimi i Vetë-Mbikëqyrur
Fusha	Mësimi i makinës	Mësimi i makinës
Familja	Machine learning	Machine learning
Viti i origjinës	1996	2018–2020
Krijuesi	Ester, M., Kriegel, H.-P., Sander, J. & Xu, X.	LeCun, Y. and community (formalized ~2018–2020)
Lloji	Density-based clustering algorithm	Representation learning paradigm
Burimi themelues	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.	LeCun, Y. & Misra, I. (2022). Self-supervised learning: The dark matter of intelligence. Meta AI Blog. https://ai.facebook.com/blog/self-supervised-learning-the-dark-matter-of-intelligence/
Emërtime të tjera	DBSCAN Kümeleme, density-based clustering, density-based spatial clustering	SSL, self-supervised pre-training, pretext-task learning, unsupervised representation learning
Të lidhura	3	3
Përmbledhja	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.	Self-supervised learning (SSL) is a machine-learning paradigm that generates its own supervisory signal directly from unlabeled data by defining an auxiliary pretext task — such as predicting masked words, rotating images, or contrasting augmented views — and uses the learned representations as a powerful starting point for downstream tasks with minimal labeled examples.