Questions tagged [movielens]

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How to recommend movies for users which are not in trainset with Surprise SVD Matrix Factorisation algo?

I'm trying to implement a Surprise SVD movie recommender system and finally deploy it on a website, where the user would rate, say 10 movies and get back the top 10 recommendations. Since I already ...
2 votes
1 answer

What is the correct way to compute hit rate in recommender systems?

I'm working with the famous Movielens 1M dataset and implemented some simple recommender algorithms. While computing the hit rate, I found that it's very low $(\approx 0.008)$ but the papers seem to ...
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precision and recall at k for movielens dataset

I wanted to recreate a very simple collaborative filtering example with the 1M movielens dataset I have from Kaggle ( and then ...
1 vote
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Dot product of two matrices in NLP how can i get this error be solved [closed]

from sklearn.metrics.pairwise import linear_kernel sim_matrix = linear_kernel(tfidf_matrix, tfidf_matrix) when I try to get dot product I am getting this errro <...
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How to estimate missing values when calculating NDCG

I would like to compare recommendations methods using NDCG metric on MovieLens dataset. In ranking problem, the goal is to rank items based on their relevance for user. Ranking models can be learned ...
1 vote
1 answer

Dealing with missing data in SVD

I am a newbie to machine learning and I am trying to apply the SVD on the movielens dataset for movie recommendation. I have a movie-user matrix where the row is the user id, the column is the movie ...
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3 votes
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memory error in matrix cosine_similarity

I have (20905040, 7) of a dataset to recommend 10 different product to the user it could be larger than that but anyway I got memory error when processing the ...
1 vote
0 answers

What is the current state of the art solution for Movielens 100k / 20M?

I found Basic recommendation system for Movilens dataset using Keras which has a solution which works ok (MAE 0.84). What is the current state of the art for this dataset?
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