python推荐算法代码

下面是一个使用Python实现的推荐算法的代码示例：

import pandas as pd
from surprise import Dataset
from surprise import Reader
from surprise import KNNBasic

# 读取评分数据
heads=['user_id','item_id','rating','timestamp']
ratings = pd.read_csv('u.data', sep='\t', names=heads)

# 创建Surprise所需的数据集
reader = Reader(rating_scale=(1, 5))
data = Dataset.load_from_df(ratings[['user_id', 'item_id', 'rating']], reader)

# 构建基于用户的协同过滤模型
sim_options = {'name': 'cosine', 'user_based': True}
model = KNNBasic(sim_options=sim_options)
trainset = data.build_full_trainset()
model.fit(trainset)

# 进行推荐
user_id = 1  # 需要为哪个用户进行推荐
n_recommendations = 5  # 推荐的电影数量

# 获取用户未评分的电影列表
rated_movies = ratings[ratings['user_id'] == user_id]['item_id']
unrated_movies = ratings<span class="em">1</span><span class="em">2</span><span class="em">3</span>
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