``{r} library(dplyr) ``` ```{r} library(tidyr) ``` ```{r} stock_df <- read.csv("stock_df.csv") ``` ```{r} stock_df_long <- stock_df %>% pivot_longer( cols = starts_with("X2019_week"), names_to = c("year", "week"), names_pattern = "X(\\d+)_week(\\d+)", values_to = "price" ) %>% mutate( year = as.integer(year), week = as.integer(week) ) ``` ```{r} head(stock_df_long) ```

LSTM predicted close price of the next trading day: 35.59

Fourth Series of Exercises

Binary Classification untuk prediksi level risiko investasi (0: low risk, 1: high risk)