[ML] Parametric model vs Non-parametric model

Parametric model : the model has fixed number of parameters

고정된 개수의 파라미터들을 학습한다. flexibility 낮음

Ex) Linear regression, Logistic regression, Bayesian inference, Neural network(CNN, RNN)등

 

Non-parmetric model : the number of parameters grow with the amount of training data

Ex) Decision tree, K-means clustering 등