id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
aiti-13355	Maria Concepcion Suarez Vera	Precision Geolocation of Medicinal Plants: Assessing Machine Learning Algorithms for Accuracy and Efficiency	2024	14	.pdf	application/pdf	6504	318	31	By employing machine learning algorithms—gradient boosting machine (GBM), random forest (RF), and support vector machine (SVM)—within the cross-industry standard process for data mining (CRISP-DM) framework, both the accuracy and efficiency of medicinal plant geolocation are enhanced. These outcomes highlight the efficacy of SVM and GBM in medicinal plant geolocation and accentuate their potential to advance environmental research, conservation strategies, and pharmaceutical explorations.	cache/aiti-13355.pdf	txt/aiti-13355.txt