#smote News & Analysis

2 articles tagged with #smote. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

2 articles

AIBullisharXiv – CS AI · Jun 96/10

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Large Language Models for Imbalanced Classification: Diversity makes the difference

Researchers have developed a novel LLM-based oversampling method to address imbalanced classification in machine learning, focusing on generating diverse synthetic minority samples. The approach outperforms existing methods like SMOTE by preserving categorical information and introducing enhanced diversity through novel sampling and fine-tuning strategies.

AIBullisharXiv – CS AI · Jun 26/10

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Improving IoT Intrusion Detection Through SMOTE-Based Oversampling and Extended Multi-Model Evaluation on Side-Channel Power Data

Researchers address critical class imbalance problems in IoT intrusion detection by applying SMOTE oversampling to power-based side-channel datasets, achieving superior detection performance with Random Forest and Extra Trees algorithms. The study demonstrates that balanced datasets reveal minority attack classes previously missed by traditional evaluation metrics, advancing security for IoT networks.