// Workers AI · dad joke modeWhat did implicit blockmodeling say to its date? You fit my model.
 | This article provides insufficient context for those unfamiliar with the subject. (September 2021) |
Implicit blockmodeling is an approach in blockmodeling, similar to a valued and homogeneity blockmodeling, where initially an additional normalization is used and then while specifying the parameter of the relevant link is replaced by the block maximum.[1]
This approach was first proposed by Batagelj and Ferligoj in 2000,[2]: 16–17 and developed by Aleš Žiberna in 2007/08.[3][4]
Comparing with homogeneity, the implicit blockmodeling will perform similarly with max-regular equivalence, but slightly worse in other settings. It will perform worse than valued and homogeneity blockmodeling with a pre-specified blockmodel.[1]
References
[edit]- 1 2 Žiberna, Aleš (2009). "Evaluation of Direct and Indirect Blockmodeling of Regular Equivalence in Valued Networks by Simulations". Metodološki zvezki. 6 (2): 99–134.
- ↑ Batagelj, Vladimir; Ferligoj, Anuška (2000). "Clustering relational data". In Gaul, W.; Opitz, O.; Schader, M. (eds.). Data Analysis. Springer Verlag. pp. 3–15.
- ↑ Aleš Žiberna, Generalized blockmodeling of valued networks (pospološeno bločno modeliranje omrežij z vrednostmi na povezavah: doktorska disertacija. Ljubljana: Univerza v Ljubljani, Fakulteta za družbene vede, 2007. URL: https://www2.arnes.si/~aziber4/blockmodeling/Dissertation-final-corrected.pdf.
- ↑ Žiberna, Aleš (2008). "Direct and indirect approaches to blockmodeling of valued networks in terms of regular equivalence". Journal of Mathematical Sociology. 32: 57–84.
 | This machine learning–related article is a stub. You can help Wikipedia by adding missing information. |