id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
easat-2307	Morić, Zlatan 	Enhancing predictive accuracy of electoral outcomes: A comparative study of dimension reduction techniques in linear regression models	2024	22	.pdf	application/pdf	12263	756	49	The importance of maintaining homoscedasticity in regression models is underscored by the findings, and the potential of dimension reduction techniques to improve electoral predictions is highlighted. Frequently employed in addressing the challenges of high-dimensional data in regression models are dimension reduction techniques such as Principal Component Analysis (PCA) and Factor Analysis (FA).	cache/easat-2307.pdf	txt/easat-2307.txt