QuestionQuestion

Write a small program to compare the methods by MN logistic regression, the LDA and QDA using the wine data. You do not have to conduct variable selection, but can choose all 13 variables or add the interactions to these 13 variables.
Use 10-fold cross-validation method to assess the performance and pay attention to the stratified sampling with the wine classes.

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library(nnet)
library(caret)
library(ggplot2)
library(MASS)
library(dplyr)
library(reshape)

set.seed(1234)

dat <- read.csv("http://archive.ics.uci.edu/ml/machine-learning-databases/wine/wine.data")

c_names <- c("Class","Alcohol", "Malic_Acid", "Ash",
          "Alcalinity_of_Ash", "Magnesium", "Total_phenols",
          "Flavanoids", "Nonflavanoid_phenols", "Proanthocyanins",
          "Color_Intensity", "Hue", "OD280/OD315", "Proline")

names(dat) <- c_names

n <- nrow(dat)
shuffled_dat <- dat[sample(n), ]
train_indices <- 1:round(0.7 * n)
wine_train <- shuffled_dat[train_indices, ]
test_indices <- (round(0.7 * n) + 1):n
wine_test <- shuffled_dat[test_indices, ]...

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