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Questions tagged [lightfm]

30 questions
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Evaluating LightFM model performance with lightfm.evaluation.precision_at_k

I am trying to use lightfm.evaluation.precision_at_k() to evaluate performance of my model. My questions are around the parameters that I need to pass to it: Does the test_interactions parameter needs to be the exact same shape (user indexes…
Pedro
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When I give the train + test set I get a precision above 1 (LightFM)

I am implementing a recommender system (python 3.9) for an online supermarket (hence users can re-order products). All the data is in the correct format which led to an interaction matrix, a weights matrix (to show the importance of some of the…
Jessica Eggen
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What is the correct way to handle cross sectional features in lightFM recommender model

UPDATED QUESTION I am trying to build a hybrid recommender system in python based on the lightFM library. The input data contains information on users, actions (things I am trying to recommend) and binary ratings. I also have user features that are…
bmasri
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How to understand the dimensions of Sparse matrix (Compressed Sparse Row format) generated in lightFM to map it to #features?

I am working on a lightFM hybrid recsys model with both user and item metadata features. These user and item features are of the format: (0, [feature1, feature2, ... feature n]) and applying them into dataset.build_user_features() and a sparse…
Barath Srinivasan
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LightFM model: scores and sigmoid function inside

I have two questions related to the LightFM model: I read the article about the model and I see that it uses sigmoid f(.)-function. I also checked library's Cython code and I see that the function is implemented there as well. However, the model is…
Anna Denisova
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DataError: No numeric types to aggregate pandas pivot

I have a pandas dataframe like this: User-Id Training-Id TrainingTaken 0 4327024 25 10 1 6662572 3 10 2 3757520 26 10 and I need to convert it to a Matrix like they do…
Luis Valencia
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ValueError: The user feature matrix specifies more features than there are estimated feature embeddings: 19400 vs 81728

I have the following datasets: Users: 10.000 Rows. Features: User-Id, name, age, los, ou, gender, skills, language, grade, career interests Trainings: Training-Id, training name, main skill Trainings Taken User-Id, Training-Id,…
Luis Valencia
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how to make an integer index corresponding to a string value?

I'm currently building a recommender system using Goodreads data. I want to change string user ids into integers. Current user ids are like this: '0d688fe079530ee1fe6fa85eab10ec5c' I want to change it into integers(e.g. 1, 2, 3, ...), to have the…
Serious
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Unable to install Lightfm

This is the error that I'm getting whenever I try to install a certain few libraries. I have tried updating my pip to the latest version. And I'm using python 3.8.5 C:\Users\Deep\Desktop\Sentiment Analysis>pip install lightfm Collecting lightfm …
Deep Patil
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What's a good way to "weight" the importance of item/user features in LightFM?

I have been using LightFM in an e-commerce application with a decent amount success. Thanks for this really cool package! I'm in the process of optimizing the recommendation outputs. Because of specific business domain considerations, certain…
Max
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Proper way to setup user-item interactions data in lightfm

What is the right way to setup the data when feeding to lightfm model for cases where I have additional implicit data on additional items/products. For example, I have 100k users x 200 items interaction data, however in real application, I want the …
bninopaul
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Standard Collaborative Filtering vs Hybrid Light FM

I'm new to recommender system and trying to understand the fundamental difference between standard collaborative filtering (CF) and hybrid methods like LightFM. As I researched online, most of the posts mentioned hybrid method combines both CF and…
ADJ
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lightfm error: Not all estimated parameters are finite, your model may have diverged

I'm running this very simple code: def csr_values_analysis(values): num_zeros = 0 num_ones = 0 num_other = 0 for v in values: if v == 0: num_zeros += 1 elif v == 1: num_ones += 1 else: …
frb
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predict new user using lightfm

I want to give a recommendation to a new user using lightfm. Hi, I've got model, interactions, item_features. The new user is not in interactions and the only information of the new user is their ratings.(list of book_id and rating pairs) I tried to…
Serious
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Recommendations are coming same before and after fit_partial for new interactions for any user lightfm

for any user let's say some new interactions come then I am fitting the dataset and model with only new interactions data using partial_fit and I am getting the same results before and after partial fit for that user.
Lalit Vyas
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