学习笔记（十二）：推荐系统-隐语义模型

最新推荐文章于 2022-06-07 15:30:14 发布

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最新推荐文章于 2022-06-07 15:30:14 发布

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分类专栏： python 机器学习推荐系统

本文链接：https://blog.youkuaiyun.com/weixin_39878297/article/details/83144128

#代码摘自唐宇迪《推荐系统》视频课程，数据集来自http://pan.baidu.com/s/1eS5VZ8Y中的“ml-1m"数据

from collections import deque
from six import next
import readers

import tensorflow as tf
import numpy as np

import time

np.random.seed(42)
u_num = 6040
i_num = 3952

batch_size = 1000
dims = 5
max_epochs = 50
place_device = "/cpu:0"

def get_data()
    df = readers.read_file("./ml-1m/ratings.dat",sep = "::")
    rows = len(df)
    df = df.iloc[np.random.permutation(rows)].reset_index(drop = True)
    split_index = int(rows*0.9)
    df_train = df[0:split_index]
    df_test = df[split_index:].reset_index(drop = True)
    return df_train,df_test

def clip(x):
    return np.clip(x, 1.0, 5.0)

def model(user_batch, item_batch, user_num, item_num, dim=5, device = "cpu:0"):
    with tf.device("/cpu:0"):
        with tf.variable_scope('lsi',reuse = True):
            bias_global = tf.get_variable("bias_global",shape=[])
            w_bias_user = tf.get_variable("embd_bias_user",shape=[user_num