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IEEE/ICACT20260019 Slide.09        [Big Slide]       [YouTube]	Oral Presentation
	Categorical features are transformed using one-hot encoding to enable efficient numerical processing by classical machine learning models. Feature correlation analysis is applied to remove redundant attributes, reducing the feature space from 41 to 35 dimensions. This reduction minimizes computational overhead and improves inference latency under SmartNIC constraints.

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