Gaussian Discriminant Analysis
[Normal Distribution](https://texonom.com/normal-distribution-46824b2fc69b4c5c8304b57a8967ce4c) [Logistic Regression](https://texonom.com/logistic-regression-8ed39aeb672648b1933df8911996d5d7) [Data Classification](https://texonom.com/data-classification-0ed6ffa3555b4879be09f0501f0b580c) 


## GDA
GDA is commonly used for data classification when the data can be approximated with a normal distribution
object is to predict posterior density by the Bayes Theorem
phi $\phi$ is parameter for prior
- class prior is Bernoulli
- class conditional distribution is Normal
estimate mean, covariance becuz continuous
$$P(y|x)=P(x|y)Pprior(y)Σg∈YP(x|g)Pprior(g)$$
special case of MoG



> [가우시안 분포와 분별 함수 (선형 분별 분석(LDA), 2차 분별 분석(QDA))](https://gaussian37.github.io/ml-concept-gaussian_discriminant/)





