运行时错误：结果的 nnz 太大

如何解决运行时错误：结果的 nnz 太大

我正在制作一个基于内容的推荐引擎。我的代码：

import numpy as np
import pandas as pd
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.metrics.pairwise import cosine_similarity

df = pd.read_csv("IMDb movies.csv",dtype='unicode')
features = ['genre','country','director','actors']

def combine_features(row):
    return row['genre']+" "+row['country']+" "+row['director']+" "+row['actors']

for x in features:
    df[x]=df[x].fillna('')

df['combined_features']=df.apply(combine_features,axis=1)
cv = CountVectorizer()
matrix = cv.fit_transform(df['combined_features'])
cosinesimilarity = cosine_similarity(matrix)

我收到以下错误：

RuntimeError: nnz of the result is too large