Krahasoni metodat

	DBSCAN	Rrjeti Neurale i Grafëve
Fusha	Mësimi i makinës	Mësimi i thellë
Familja	Machine learning	Machine learning
Viti i origjinës	1996	2017
Krijuesi	Ester, M., Kriegel, H.-P., Sander, J. & Xu, X.	Kipf, T.N. & Welling, M.
Lloji	Density-based clustering algorithm	Deep learning on graph-structured data
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.	Kipf, T.N. & Welling, M. (2017). Semi-Supervised Classification with Graph Convolutional Networks. ICLR.
Emërtime të tjera	DBSCAN Kümeleme, density-based clustering, density-based spatial clustering	Grafik Sinir Ağı (GNN), GNN, graph neural net, graph convolutional network
Të lidhura	3	4
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.	A Graph Neural Network (GNN) is a deep learning method, popularised by Kipf and Welling in 2017 with the Graph Convolutional Network, that learns from the relationships in network (graph) structures made of nodes and edges. It is designed for data that is naturally relational, such as social networks, molecular structures, and recommendation systems.