결측값(missing value) handling
Boston data [missing vlaue generation] 1. deleting the observations 2. deleting the variable [missing vlaue handling] 3. imputation with mean/median/mode 4. prediction 4.1 KNN imputation 4.2 rpart : decision tree 5. evaluation verification 5.1 mean imputation 5.2 KNN imputation 5.3 rpart R Code ### Missing Values ####### # initialize the data # load the data install.packages("MASS") library(MASS) data(Boston) dim(Boston) original <- Boston # backup original data # Introduce missing values set.seed(100) Boston[sample(1:nrow(Boston), 40), "rad"] <- NA Boston[sample(1:nrow(Boston), 40), "ptratio"] <- NA head(Boston) # 1. Deleting the observations, if na exist na.omit action, when use lm, omit is default # lm(medv ~ ptratio + rad, data=Boston, na.action=na.omit) lm(medv ~ ptratio + rad, data=Boston) ## 2. Deleting the variable ## when variable missing is many, the variable elim...