In zaenalium/rewlr: Rare Event Weighted Logistics Regression

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

Load data & package

library(rewlr)

data("National_exam_id")

Pembagian training dan testing

Pembagian testing dan training menggunakan metode stratified sampling dan based choiced sampling

Berikut adalah pembagian testing dan training berdasarkan stratified sampling

s <- sample(1:nrow(National_exam_id), nrow(National_exam_id) * 0.5)


train <- National_exam_id[s, ]
test <- National_exam_id[-s, ]

Pemodelan menggunakan rewlr

#tau <- sum(National_exam_id$y == 1)/length(National_exam_id$y)
#y_bar <- sum(train$y == 1)/length(train$y)

#tau <- 0.13
#y_bar <- 0.1
#(weight0 = (1 - tau)/(1-y_bar))
#(weight1 = (tau)/(y_bar))
#iter = 1000; tol = 0.00001

#fit <- rewlr(y~., data = train, weights0 = weight0, weights1 = weight1,
#             tol = 1e-06, iter = 1000, lambda = 1)
#summary(fit)
#pred_train <- predict(fit)


#tb <- table(predict = ifelse(pred_train < 0.5, 0, 1), actual = train$y)
#tb