id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
cana-4022	Roshni Verma	Supervised Vs. Unsupervised Learning: A Comparative Study in Modern AI System	2025	13	.pdf	application/pdf	5264	278	44	Hypothesis The study formulates the following hypotheses to test the comparative performance of supervised and unsupervised learning models: H1: Supervised learning models (Decision Trees, SVM) will exhibit significantly higher accuracy and lower error rates than unsupervised learning models (K-Means, Autoencoders). Such unsupervised learning models as k-means clustering and autoencoders could also be mentioned.	cache/cana-4022.pdf	txt/cana-4022.txt