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Machine learning

Ukusanyaji wa Kikundi kwa Njia ya Spektra (Spectral Clustering)

Ukusanyaji wa Kikundi kwa Njia ya Spektra ni algoriti ya ujifunzaji usiosimamiwa inayotegemea grafu, iliyorasimishwa na Ng, Jordan, na Weiss mnamo 2002, ambayo hupanga pointi za data katika nafasi ya eigenspace yenye vipimo vichache inayotokana na Laplacian ya grafu ya kufanana kabla ya kutumia k-means. Upachikaji huu wa spektra unawezesha kugundua vikundi vya maumbo mbalimbali — pete, hilali, spirali zilizoungana — ambavyo mbinu zinazotegemea umbali wa Euclidean hushindwa kuvitenganisha.

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Vyanzo

  1. Ng, A. Y., Jordan, M. I., & Weiss, Y. (2002). On Spectral Clustering: Analysis and an Algorithm. Advances in Neural Information Processing Systems, 14, 849–856. link
  2. von Luxburg, U. (2007). A Tutorial on Spectral Clustering. Statistics and Computing, 17, 395–416. DOI: 10.1007/s11222-007-9033-z
  3. Shi, J., & Malik, J. (2000). Normalized Cuts and Image Segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(8), 888–905. DOI: 10.1109/34.868688

Jinsi ya kunukuu ukurasa huu

ScholarGate. (2026, June 3). Spectral Clustering via Graph Laplacian Eigenvectors (Ng–Jordan–Weiss Algorithm). ScholarGate. https://scholargate.app/sw/machine-learning/spectral-clustering

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Imerejelewa na

ScholarGateSpectral Clustering (Spectral Clustering via Graph Laplacian Eigenvectors (Ng–Jordan–Weiss Algorithm)). Imepatikana 2026-06-15 kutoka https://scholargate.app/sw/machine-learning/spectral-clustering · Seti ya data: https://doi.org/10.5281/zenodo.20539026