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Machine learningSymbolic data

Uchambuzi wa Data ya Alama

Uchambuzi wa Data ya Alama (SDA) ni mfumo wa takwimu uliobuniwa kuchambua data tata, zilizojumuishwa, au zenye thamani za seti — zinazoitwa data ya alama — ambapo kila uchunguzi unawakilisha kundi au dhana badala ya nambari moja. Ulioanzishwa katika mfumo wake wa kisasa wa takwimu na Lynne Billard na Edwin Diday mwaka 2003, SDA hupanua takwimu za kawaida kushughulikia vigezo vyenye thamani za kipindi, histogramu, na vingi, kuwezesha hitimisho sahihi katika kiwango cha maarifa badala ya rekodi za mtu binafsi.

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Uchambuzi wa Data ya Alama
Uchanganuzi wa Data za K…

Vyanzo

  1. Billard, L., & Diday, E. (2003). From the statistics of data to the statistics of knowledge: symbolic data analysis. Journal of the American Statistical Association, 98(462), 470–487. DOI: 10.1198/016214503000242

Jinsi ya kunukuu ukurasa huu

ScholarGate. (2026, June 2). Symbolic Data Analysis (SDA). ScholarGate. https://scholargate.app/sw/soft-computing/symbolic-data-analysis

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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.

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Imerejelewa na

ScholarGateSymbolic Data Analysis (Symbolic Data Analysis (SDA)). Imepatikana 2026-06-15 kutoka https://scholargate.app/sw/soft-computing/symbolic-data-analysis · Seti ya data: https://doi.org/10.5281/zenodo.20539026