Bias 은 예측값과 정답의 차이 정도, Variance 은 예측값끼리의 차이 정도
과소적합(Underfitting): High bias
과적합(Overfitting): High variance
MSE = Bias + Variance
Bias-Variance Tradeoff!



https://towardsdatascience.com/understanding-the-bias-variance-tradeoff-165e6942b229?gi=3507c8a8e592
Understanding the Bias-Variance Tradeoff
Whenever we discuss model prediction, it’s important to understand prediction errors (bias and variance). There is a tradeoff between a…
towardsdatascience.com
https://velog.io/@iguv/Bias-and-Variance#:~:text=Bias%20%EC%9D%80%20%EC%98%88%EC%B8%A1%EA%B0%92%EA%B3%BC%20%EC%A0%95%EB%8B%B5%EC%9D%98%20%EC%B0%A8%EC%9D%B4%20%EC%A0%95%EB%8F%84%2C%20Variance%20%EC%9D%80,%ED%95%A9%EC%9D%80%20High%20variance%20%EC%9D%B4%EB%8B%A4.
https://modulabs-biomedical.github.io/Bias_vs_Variance
'AI > Data Science' 카테고리의 다른 글
hugging face / Qwen2 snippent code (0) | 2024.06.17 |
---|---|
가설검증 Hypothesis Testing (귀무가설 / 유의수준 / p값 / 제1종의 오류, 제2종의 오류) (0) | 2024.06.03 |
[Statistics] MGF(Moment Generating Function), Binomial Theorem (1) | 2024.05.23 |
[Statistics] 극좌표계, 직교좌표계, 야코비 행렬 등 응용하는 적분문제,, (0) | 2024.04.29 |
[Statistics] Bivariate / Multivariate 확률분포 / IID (0) | 2024.04.21 |