Re: 오늘의 마지막 문제. 지금 만든 나이브 베이즈 알 샤이니 화면을 쳇GPT 에게 요청해서..

[19기_이승원]

if (!require("shiny")) install.packages("shiny")
if (!require("naivebayes")) install.packages("naivebayes")
if (!require("e1071")) install.packages("e1071")
if (!require("caret")) install.packages("caret")

library(shiny)
library(naivebayes)
library(e1071)
library(caret)

# 데이터 불러오기
movie <- read.csv("c:\\data\\movie2.csv", stringsAsFactors=TRUE, fileEncoding = "euc-kr")

# 결측치 확인
colSums(is.na(movie))

# 훈련 데이터와 테스트 데이터로 분리
set.seed(1)
k <- createDataPartition(movie$장르, p=0.8, list=FALSE)
train_data <- movie[k, ]
test_data <- movie[-k, ]

# 나이브 베이즈 모델 생성
new_model <- naive_bayes(장르 ~ ., data=train_data)

# UI 정의
ui <- fluidPage(
  tags$head(
    tags$style(HTML("
      .title {
        text-align: center;
      }
      .seagreen-button {
        background-color: seagreen;
        color: white;
        border-color: seagreen;
        font-weight: bold;
      }
    "))
  ),
  titlePanel("영화 장르 예측기", windowTitle = "영화 장르 예측기"),
  fluidRow(
    column(2,
      selectInput("age", "나이", choices = unique(movie$나이))
    ),
    column(2,
      selectInput("gender", "성별", choices = unique(movie$성별))
    ),
    column(2,
      selectInput("job", "직업", choices = unique(movie$직업))
    ),
    column(2,
      selectInput("married", "결혼 여부", choices = unique(movie$결혼여부))
    ),
    column(2,
      selectInput("relationship", "이성 친구 여부", choices = unique(movie$이성친구))
    )
  ),
  fluidRow(
    column(12, align = "center",
      actionButton("predict", "예측하기", class = "seagreen-button")
    )
  ),
  fluidRow(
    column(12,
      verbatimTextOutput("prediction"),
      textOutput("top_genre")
    )
  )
)

# 서버 로직 정의
server <- function(input, output) {
  
  observeEvent(input$predict, {
    test_data <- data.frame(
      나이 = input$age,
      성별 = input$gender,
      직업 = input$job,
      결혼여부 = input$married,
      이성친구 = input$relationship
    )
    
    result <- predict(new_model, test_data, type = "prob")
    
    output$prediction <- renderPrint({
      result
    })
    
    output$top_genre <- renderText({
      top_genre_index <- which.max(result[1, ])  # 첫 번째 예측 결과의 가장 높은 확률을 가진 장르 인덱스
      top_genre_name <- colnames(result)[top_genre_index]  # 해당 인덱스에 해당하는 장르 이름
      paste("가장 높은 확률을 가진 장르:", top_genre_name)
    })
  })
  
}

# Shiny 앱 실행
shinyApp(ui = ui, server = server)