Undersampling: 편집 역사

2024년 11월 5일 (화)

• 최신이전 06:502024년 11월 5일 (화) 06:50‎ 핵톤 토론 기여‎ 5,426 바이트 +5,426‎ Created page with "'''Undersampling is a technique used in data science and machine learning to address class imbalance by reducing the number of samples in the majority class'''. Unlike oversampling, which increases the representation of the minority class, undersampling aims to balance the dataset by removing instances from the majority class. This technique is commonly applied in scenarios where the majority class significantly outnumbers the minority class, such as fraud detection..." 태그: 시각 편집