我有一個帶有電影評論的文本變數和另一個帶有評分的變數——我想嘗試使用文本評論來預測評分。
以下是一些示例資料：
movie_reviews <- c("I really loved the movie plot", "This movie really sucked", "I really found this movie thought provoking", "ahh what a boring movie", "A wonderful movie, with a wonderful end", "Great action movie: Very thrilling", "Worst movie ever, it never stopped being cheesy", "Enjoying, feelgood movie for the entire family", "I will definitely watch this movie again")
movie_ratings <- c(8, 2, 6, 3, 9, 8.5, 3.5, 9.5, 7.5)
movie_df <- tibble(movie_reviews, movie_ratings)
謝謝你。
uj5u.com熱心網友回復：
為此，您可以使用text-package
# Create word embedding representations of your text
help(textEmbed)
reviews_embeddings <- textEmbed(movie_df,
model = "bert-base-uncased", # Select model you want from huggingface
layers = 11:12) # Select which layers you want to use
# Train the word embeddings to the numeric variable using ridge regression
reviews_rating_model <- textTrain(reviews_embeddings$movie_reviews,
movie_df$movie_ratings)
# See the results
reviews_rating_model
結果
$results
Pearson's product-moment correlation
data: predy_y$predictions and predy_y$y
t = 5.621, df = 7, p-value = 0.0003991
alternative hypothesis: true correlation is greater than 0
95 percent confidence interval:
0.6785761 1.0000000
sample estimates:
cor
0.9047823
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