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Machine learningGraph mining

Kerneli za Grafu

Kerneli za grafu ni utendaji wa kerneli wenye uhakika chanya ambao hupima kufanana kati ya grafu mbili kwa kulinganisha sehemu zao za pamoja — kama vile matembezi ya nasibu, njia fupi zaidi, au ruwaza za miti midogo. Zilianzishwa katika mfumo wa umoja na Vishwanathan, Schraudolph, Kondor, na Borgwardt (2010), zinajumuisha mbinu za kerneli na data yenye muundo wa grafu, kuwezesha algoriti kama SVMs kufanya kazi moja kwa moja kwenye grafu bila kuhitaji hatua ya uwekaji kwenye vekta.

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Method map

The neighbourhood of related methods — select a node to explore.

Vyanzo

  1. Vishwanathan, S. V. N., Schraudolph, N. N., Kondor, R., & Borgwardt, K. M. (2010). Graph kernels. Journal of Machine Learning Research, 11, 1201–1242. link

Jinsi ya kunukuu ukurasa huu

ScholarGate. (2026, June 2). Graph Kernels for Structured Data. ScholarGate. https://scholargate.app/sw/network-analysis/graph-kernels

Which method?

Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.

Compare side by side
ScholarGateGraph Kernels (Graph Kernels for Structured Data). Imepatikana 2026-06-15 kutoka https://scholargate.app/sw/network-analysis/graph-kernels · Seti ya data: https://doi.org/10.5281/zenodo.20539026