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Questions tagged [matrix-factorization]

In the mathematical discipline of linear algebra, a matrix decomposition or matrix factorization is a factorization of a matrix into a product of matrices.

In the mathematical discipline of linear algebra, a matrix decomposition or matrix factorization is a factorization of a matrix into a product of matrices.

In numerical analysis, different decompositions are used to implement efficient matrix algorithms.

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Sklearn train_test_split; retaining unique values from column(s) in training set

Is there a way to use sklearn.model_selection.train_test_split to retain all unique values from a specific column(s) in the training set. Let me set up an example. The most common matrix factorization problem I am aware of is predicting movie…
Grr
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Python Non negative Matrix Factorization that handles both zeros and missing data?

I look for a NMF implementation that has a python interface, and handles both missing data and zeros. I don't want to impute my missing values before starting the factorization, I want them to be ignored in the minimized function. It seems that…
Théo T
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Cholesky decomposition of sparse matrices using permutation matrices

I am interested in the Cholesky decomposition of large sparse matrices. The problem I'm having is that the Cholesky factors are not necessarily sparse (just like the product of two sparse matrices is not necessarily sparse). For example for a matrix…
Z boson
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How to compare predictive power of PCA and NMF

I would like to compare the output of an algorithm with different preprocessed data: NMF and PCA. In order to get somehow a comparable result, instead of choosing just the same number of components for each PCA and NMF, I would like to pick the…
Phil D
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Lightfm: handling user and item cold-start

I remember one of the strong points of lightfm is that the model does not suffer from cold start problem, both user and item cold start: lightfm original paper However, I still don't understand how to use lightfm to address the cold start problem.…
bohr
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Using matrix factorization for a recommender system

I'm working on a recommender system for restaurants using an item-based collaborative filter in C# 6.0. I want to set up my algorithm to perform as well as possible, so I've done some research on different ways to predict ratings for restaurants the…
user4189129
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sklearn matrix factorization example

I am using a code currently given at http://www.quuxlabs.com/blog It gives good result. And I can clearly see what changes in the matrix has happened . Also I tried to use sklearn library at sklearn.decomposition.NMF But results I got with the same…
user2952821
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Sympy: Solving Matrices in a finite field

For my project, I need to solve for a matrix X given matrices Y and K. (XY=K) The elements of each matrix must be integers modulo a random 256-bit prime. My first attempt at solving this problem used SymPy's mod_inv(n) function. The problem with…
arnbobo
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Evaluating the LightFM Recommendation Model

I've been playing around with lightfm for quite some time and found it really useful to generate recommendations. However, there are two main questions that I would like to know. to evaluate the LightFM model in case where the rank of the…
bohr
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`Optimal` variable initialization and learning rate in Tensorflow for matrix factorization

I'm trying a very simple optimization in Tensorflow- the problem of matrix factorization. Given a matrix V (m X n), decompose it into W (m X r) and H (r X n). I'm borrowing a gradient descent based tensorflow based implementation for matrix…
Nipun Batra
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Very Large and Very Sparse Non Negative Matrix factorization

I have a very large and also sparse matrix (531K x 315K), the number of total cells is ~167 Billion. The non-zero values are only 1s. Total number of non-zero values are around 45K. Is there an efficient NMF package to solve my problem? I know there…
mgokhanbakal
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How to deal with missing values in python scikit NMF

I am trying to apply NMF on my dataset, using python scikit-learn. My dataset contains 0 values and missing values. But scikit-learn does not allow NaN value in data matrix. Some posts said that replace missing values with zeros. my questions…
Zhaojie Tao
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Vowpal Wabbit: Low-rank matrix factorization?

I have a very basic question. I'd like to do low-rank matrix factorization and I was looking at the Vowpal Wabbit documentation on the topic. My question is: Is there a difference between these two approaches? (implementation or otherwise) $ vw…
Kris
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Recommendation system with matrix factorization for huge data gives MemoryError

I have three DB models (from Django) that can be used as the input for building a recommendation system: Users List - with userId, username, email etc Movies List - with movieId, movieTitle, Topics etc Saves List - with userId, movieId and…
Vlad
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Write a trackable R function that mimics LAPACK's dgetrf for LU factorization

There is no LU factorization function in R core. Although such factorization is a step of solve, it is not made explicitly available as a stand-alone function. Can we write an R function for this? It needs mimic LAPACK routine dgetrf. Matrix package…
Zheyuan Li
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