Enhancing Olive Phenology Prediction: Leveraging Market Basket Analysis and Weighted Metrics for Optimal Feature Group Selection

Autor:	Izar Azpiroz, Marco Quartulli, Igor G. Olaizola
Jazyk:	angličtina
Rok vydání:	2023
Předmět:	market basket analysis wrapper feature selection machine learning centrality metrics graph analysis Technology Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
Zdroj:	Applied Sciences, Vol 13, Iss 19, p 10987 (2023)
Druh dokumentu:	article
ISSN:	13191098 2076-3417
DOI:	10.3390/app131910987
Popis:	Similarly efficient feature groups occur in prediction procedures such as Olive phenology forecasting. This study proposes a procedure that can be used to extract the most representative feature grouping from Market Basket Analysis-derived methodologies and other techniques. The computed association patterns in this process are visualized through graph analytic tools, comparing centrality metrics and spacial distribution approaches. Finally, highlighted feature formations are located and analyzed within the efficiency distribution of all proposed feature combinations for validation purposes.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/f43c62d8a8ee49ad97aa05cc41a18cbd Zobrazit plný text záznamu View record in DOAJ