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IEEE/ICACT20260241 Slide.18        [Big Slide]	Oral Presentation
	But accuracy is not everything; we must consider computational cost. The simplest models, like decision trees and naïve Bayes, are the fastest to train and test. The most complex models, like Gaussian process regression and neural networks, offer high accuracy but at a significant cost in memory and processing time. Linear models provided an excellent balance of adequate speed and reasonable performance.

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