从数据框创建稀疏矩阵 [英] Create Sparse Matrix from a data frame

问题描述

我正在做一项作业，试图为Netflix奖品数据建立协作过滤模型.我正在使用的数据在CSV文件中，我可以轻松地将其导入到数据框中.现在，我需要做的是创建一个稀疏矩阵，该矩阵由用户"作为行，电影"作为列，每个单元格都由相应的评估值填充.当我尝试映射数据帧中的值时，我需要为数据帧中的每一行运行一个循环，这在R中花费了大量时间，请有人可以提出一种更好的方法.这是示例代码和数据:

I m doing an assignment where I am trying to build a collaborative filtering model for the Netflix prize data. The data that I am using is in a CSV file which I easily imported into a data frame. Now what I need to do is create a sparse matrix consisting of the Users as the rows and Movies as the columns and each cell is filled up by the corresponding rating value. When I try to map out the values in the data frame I need to run a loop for each row in the data frame, which is taking a lot of time in R, please can anyone suggest a better approach. Here is the sample code and data:

buildUserMovieMatrix <- function(trainingData)
{
  UIMatrix <- Matrix(0, nrow = max(trainingData$UserID), ncol = max(trainingData$MovieID), sparse = T);
  for(i in 1:nrow(trainingData))
  {
    UIMatrix[trainingData$UserID[i], trainingData$MovieID[i]] = trainingData$Rating[i];
  }
  return(UIMatrix);
}

要从中创建稀疏矩阵的数据帧中的数据样本:

Sample of data in the dataframe from which the sparse matrix is being created:

    MovieID UserID  Rating
1       1      2       3
2       2      3       3
3       2      4       4
4       2      6       3
5       2      7       3

所以最终我想要这样的东西: 列是电影ID，行是用户ID

So in the end I want something like this: The columns are the movie IDs and the rows are the user IDs

    1   2   3   4   5   6   7
1   0   0   0   0   0   0   0
2   3   0   0   0   0   0   0
3   0   3   0   0   0   0   0
4   0   4   0   0   0   0   0
5   0   0   0   0   0   0   0
6   0   3   0   0   0   0   0
7   0   3   0   0   0   0   0

因此，解释是这样的:用户2将电影1评为3星，用户3将电影2评为3星，依此类推，其他用户和电影也是如此.我的数据框中大约有8500000行，我的代码只需要30-45分钟即可创建此用户项矩阵，我想得到任何建议

So the interpretation is something like this: user 2 rated movie 1 as 3 star, user 3 rated the movie 2 as 3 star and so on for the other users and movies. There are about 8500000 rows in my data frame for which my code takes just about 30-45 mins to create this user item matrix, i would like to get any suggestions

推荐答案

Matrix包具有一个专门为您的数据类型制作的构造函数:

The Matrix package has a constructor made especially for your type of data:

library(Matrix)
UIMatrix <- sparseMatrix(i = trainingData$UserID,
                         j = trainingData$MovieID,
                         x = trainingData$Rating)

---

否则，您可能想了解[函数的那个​​很酷的功能，即矩阵索引.您可以尝试:

---

Otherwise, you might like knowing about that cool feature of the [ function known as matrix indexing. Your could have tried:

buildUserMovieMatrix <- function(trainingData) {
  UIMatrix <- Matrix(0, nrow = max(trainingData$UserID),
                        ncol = max(trainingData$MovieID), sparse = TRUE);
  UIMatrix[cbind(trainingData$UserID,
                 trainingData$MovieID)] <- trainingData$Rating;
  return(UIMatrix);
}

(但是我绝对会推荐sparseMatrix方法.)

(but I would definitely recommend the sparseMatrix approach over this.)

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