使用 linear_kernel 时 Scikit-learn 崩溃

如何解决使用 linear_kernel 时 Scikit-learn 崩溃

我正在学习以下教程：

https://www.datacamp.com/community/tutorials/recommender-systems-python

当我尝试运行基于内容的推荐代码时，执行停止在终端上输出“Killed”，有人说这是内存不足问题。但是我的机器上有 16GB 的 RAM，我怀疑这会不会是个问题。

代码在此代码段的最后一行崩溃：

#Construct the required TF-IDF matrix by fitting and transforming the data
tfidf_matrix = tfidf.fit_transform(Metadata['overview'])

#Output the shape of tfidf_matrix
print(tfidf_matrix.shape)


#Array mapping from feature integer indices to feature name.
tfidf.get_feature_names()[5000:5010]


# Compute the cosine similarity matrix   (THE LINE BELOW CRASHES)
cosine_sim = linear_kernel(tfidf_matrix,tfidf_matrix) 

终端输出这个：

5.618207215134185
160.0
0    Led by Woody,Andy's toys live happily in his ...
1    When siblings Judy and Peter discover an encha...
2    A family wedding reignites the ancient feud be...
3    Cheated on,mistreated and stepped on,the wom...
4    Just when George Banks has recovered from his ...
Name: overview,dtype: object
(45466,75827)
Killed

我试过改变

Metadata = pd.read_csv('movies_Metadata.csv',low_memory=False)

到

Metadata = pd.read_csv('movies_Metadata.csv',low_memory=True)

但这没有用。

我需要更改什么才能在不挂起的情况下执行代码？