지도학습 개요

 Supervised Learning  Unsupervised Learning  Reinforcement Learning  Deep learning  KNN (k-neariest neigbor)  OLS (Ordinary least square)  Ridge regression  Lasso regression  Elastic net  SVM (support vector machine)  Logistic regression  decision tree  Ensemble  Voting(mix model, soft, hard)  Bagging  Random forest  Boosting  GB (Gradient boosting)  XGB (Extreme gradient boosting)  model 평가 방법 (regression, classificaion, PSNR)  confusion matrix, ROC  R2, MAE, MSE, SSE, p-value!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!  모델 fitting 방법  GB, SGB, normal equation  Convexity  Cross validation choose best hyper parameter  SVD (singular value decomposition)  PCA  LDA  QDA  Clustering  Sklearn  pipline  Grid search cross validation  Early stop  Regularization vs standardlization vs normalization  Overfitting underfitting  Curse of demension  Bias variance  Outlier  Cost, loss, object function