Enhancing Olive Phenology Prediction: Leveraging Market Basket Analysis and Weighted Metrics for Optimal Feature Group Selection
Egileak: Azpiroz. Izar
Data: 01.01.2023
Applied Sciences (Switzerland)
Abstract
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.
BIB_text
author = {Azpiroz. Izar},
title = {Enhancing Olive Phenology Prediction: Leveraging Market Basket Analysis and Weighted Metrics for Optimal Feature Group Selection},
journal = {Applied Sciences (Switzerland)},
pages = {20},
volume = {Vol. 13},
keywds = {
centrality metrics; graph analysis; machine learning; market basket analysis; wrapper feature selection
}
abstract = {
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.
}
doi = {10.3390/app131910987},
date = {2023-01-01},
}
