Using R programming, how to build a machine learning model which is regression model to this dataset? Please provide the coding!

The dataset: https://drive.google.com/file/d/1E6GwnidPJxSNzjz8PuOMx6LBhek2z0sa/view?usp=share_link

Retrieved from: https://data.oecd.org/price/housing-prices.htm

I tried to build a machine learning model which is classification model to this dataset using the following code but it come out as error. Please fix the code as well:

# load the data

data <- read.csv("housing_prices.csv")

# split the data into training and test sets

library(caret)

set.seed(123)

split_index <- createDataPartition(data$housing_prices, p = 0.8, list = FALSE)

train_data <- data[split_index, ]

test_data <- data[-split_index, ]

# train a random forest model

library(randomForest)

model <- randomForest(housing_prices ~ ., data = train_data)

# make predictions on the test data

predictions <- predict(model, test_data)

# evaluate the model using confusion matrix and other metrics

library(caret)

confusionMatrix(predictions, test_data$housing_prices)