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Questions - recommendation-engine

preparing product purchase data for pyspark ALS implicit recommendations

I'm trying to build a product recommender. I'm using a pyspark ml recommendation ALS matrix factorization model. I have data like the example data below, where I have customer and product id and the...
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user3476463

pyspark

recommendation-engine

apache-spark-ml

matrix-factorization

Votes: 0

Answers: 1

Latest Answer

See if you don't have fixed value in rating column ( explicit or implicit) you will get the prediction value in same way. Example : initially i have rating 0,1,2,3 so i was getting prediction value ( ...
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Sachin Tiwari

How to use custom item identifiers in NearestNeighbors of sckit-learn

I use sckit-learn NearestNeighbors as a recommendation engine of movies, with Movie Lens database. The recommendation engine is an item-item based recommander (neighbors of one item are other items). ...
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vittorio

pandas

scikit-learn

knn

recommendation-engine

nearest-neighbor

Votes: 0

Answers: 1

Latest Answer

Indeed, sklearn converts to numpy arrays. They have made strides toward keeping additional information (column names), but processing will probably continue to be in numpy for its efficiency. I would ...
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Ben Reiniger

How to evaluate hashtag recommendation system using MAP@K and MAR@K?

I am working on building a hashtag recommendation system. I am looking into what are the best ways I can evaluate the system. The problem statement is: For a given hashtag I need to recommend most rel...
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Vishal Anand

python

evaluation

mahout-recommender

recommendation-engine

Votes: 0

Answers: 1

Latest Answer

Answers: perhaps, read-on "cross-validation" tests like MAP@k require that the data is split into "test" and "training" data. save 20% of the data for the "test&quo...
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Pat Ferrel

Determining cosine similarity for large datasets

I am currently using a dataset of over 2.5 million images, of which I use the image itself as a comparison to eachother, for use in a content-based recommendation engine. I use the following code to c...
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pippinpaddleopsicopolis

python

machine-learning

deep-learning

recommendation-engine

cosine-similarity

Votes: 0

Answers: 2

Latest Answer

You have 2,500,000 entries. So resulting matrix has 6.25e+12 entries. You need to ask yourself what do you plan to do with this data, compute only what you need, and then the storage will follow. Comp...
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lejlot

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