Taarifa Iliyounganika Iliyopimwa
Taarifa Iliyounganika inatoa kiasi cha habari ambacho kujua lebo za ukweli kunapunguza kutokuwa na uhakika kuhusu mgao wa makundi, na kinyume chake. NMI hupima kiasi hiki ili kiweze kulinganishwa katika seti tofauti za data na usambazaji wa lebo. Uelewa muhimu ni kwamba ikiwa kuunganisha makundi kutatabiri ukweli kikamilifu, taarifa iliyounganika itakuwa kubwa zaidi. NMI huanzia 0 (hakuna makubaliano) hadi 1 (makubaliano kamili), na kuifanya iwe rahisi kuelewa na kulinganisha katika tafiti.
Soma mbinu kamili
Ingia kwa akaunti ya bure ili kusoma sehemu hii.
Method map
The neighbourhood of related methods — select a node to explore.
Vyanzo
- Danon, L., Diaz-Guilera, A., Duch, J., & Arenas, A. (2005). Comparing community structure identification. Journal of Statistical Mechanics: Theory and Experiment, 2005(09), P09008. DOI: 10.1088/1742-5468/2005/09/P09008 ↗
Jinsi ya kunukuu ukurasa huu
ScholarGate. (2026, June 3). Normalized Mutual Information for Clustering Agreement. ScholarGate. https://scholargate.app/sw/model-evaluation/normalized-mutual-information
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.
- Kielelezo cha Rand KilichorekebishwaTathmini ya Modeli↔ compare
- Kielezo cha Davies-BouldinTathmini ya Modeli↔ compare
- Kielezo cha Fowlkes-MallowsTathmini ya Modeli↔ compare
- Kiwango cha SilhouetteTathmini ya Modeli↔ compare
- V-measureTathmini ya Modeli↔ compare
Imerejelewa na
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