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

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...

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Bibliographic Details
Published in:Applied sciences 2023-10, Vol.13 (19), p.10987
Main Authors: Azpiroz, Izar, Quartulli, Marco, Olaizola, Igor G.
Format: Article
Language:English
Subjects:
centrality metrics
Data mining
Datasets
Efficiency
Feature selection
graph analysis
Machine learning
market basket analysis
Methods
Phenology
Sea level
Trends
wrapper feature selection
Citations: Items that this one cites
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Summary: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.
ISSN:2076-3417
2076-3417
DOI:10.3390/app131910987