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I'm have matrix data containing some null values. To fill the null values, I'd like to perform collaborative filtering. As I am studying for R, rather I'd like to use R.
So, Does anyone know how to perform collaborative filtering in R?
482
asked May 26 '12 14:05
Collaborative filtering (CF) uses the known preference of a group of users to make predictions and recommendations about the unknown preferences of other users (recommendations are made based on the past behavior of users).
Model-based Collaborative Filtering These system algorithms are based on machine learning to predict unrated products by customer ratings. These algorithms are further divided into different subsets, i.e., Matrix factorization-based algorithms, deep learning methods, and clustering algorithms.
To calculate IBCF based on movie ratings, first, we will calculate normalize ratings by subtracting item ratings with user's average rating. This will standardize ratings to the same scale. Next, we'll calculate the similarity of each item by passing the actual rating and normalized rating to our 'calCosine' function.
Like Ben Bolker said, recommenderlab is the package in R that you can use. A detailed document for the same is available at http://cran.r-project.org/web/packages/recommenderlab/vignettes/recommenderlab.pdf
141
answered Sep 28 '22 03:09
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