Bias-Variance Trade-Off: 편집 역사

2024년 11월 5일 (화)

• 최신이전 07:492024년 11월 5일 (화) 07:49‎ 핵톤 토론 기여‎ 6,277 바이트 +6,277‎ Created page with "The Bias-Variance Trade-Off is a fundamental concept in machine learning that describes the balance between two sources of error that affect model performance: bias and variance. The goal is to achieve a balance between bias and variance that minimizes the model’s total error, enabling it to generalize well to new, unseen data. ==Understanding Bias and Variance== *'''Bias''': Refers to the error introduced by approximating a complex real-world problem with a simplified..." 태그: 시각 편집