Kigezo cha Taarifa cha Akaike (AIC)
Kigezo cha Taarifa cha Akaike ni kipimo cha nadharia ya taarifa kwa ajili ya uteuzi wa modeli ambacho kinasawazisha ubora wa kufaa dhidi ya ugumu wa modeli. Kilitambulishwa na Hirotugu Akaike mwaka 1974, AIC kinatathmini ubora wa kulinganisha wa modeli kwa seti fulani ya data, kikitoza adhabu kwa vigezo vya ziada ili kuzuia overfitting.
Soma mbinu kamili
Ingia kwa akaunti ya bure ili kusoma sehemu hii.
Ramani ya mbinu
Jirani ya mbinu zinazohusiana — chagua nodi ili kuchunguza.
Vyanzo
- Akaike, H. (1974). A new look at the statistical model identification. IEEE Transactions on Automatic Control, 19(6), 716-723. DOI: 10.1109/TAC.1974.1100705 ↗
- Burnham, K. P., & Anderson, D. R. (2002). Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach (2nd ed.). New York: Springer. DOI: 10.2307/3802723 ↗
- Kullback, S., & Leibler, R. A. (1951). On information and sufficiency. Annals of Mathematical Statistics, 22(1), 79-86. DOI: 10.1214/aoms/1177729694 ↗
Jinsi ya kunukuu ukurasa huu
ScholarGate. (2026, June 3). Akaike Information Criterion. ScholarGate. https://scholargate.app/sw/model-evaluation/akaike-information-criterion
Mbinu ipi?
Weka mbinu hii kando ya jamaa zake wa karibu na uzisome bega kwa bega — maktaba huweka vitabu mezani; uamuzi ni wako.
- R² iliyorekebishwa (R²_adj)Tathmini ya Modeli↔ linganisha
- Kigezo cha Taarifa cha Bayesian (BIC)Tathmini ya Modeli↔ linganisha
- Kosa la Wastani Lililopigwa Mraba (MSE)Tathmini ya Modeli↔ linganisha
- R-squared (R²)Tathmini ya Modeli↔ linganisha
Imerejelewa na
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