Other packages > Find by keyword >

cmfrec  

Collective Matrix Factorization for Recommender Systems
View on CRAN: Click here


Download and install cmfrec package within the R console
Install from CRAN:
install.packages("cmfrec")

Install from Github:
library("remotes")
install_github("cran/cmfrec")

Install by package version:
library("remotes")
install_version("cmfrec", "3.5.1-3")



Attach the package and use:
library("cmfrec")
Maintained by
David Cortes
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-11-23
Latest Update: 2023-12-09
Description:
Collective matrix factorization (a.k.a. multi-view or multi-way factorization, Singh, Gordon, (2008) ) tries to approximate a (potentially very sparse or having many missing values) matrix 'X' as the product of two low-dimensional matrices, optionally aided with secondary information matrices about rows and/or columns of 'X', which are also factorized using the same latent components. The intended usage is for recommender systems, dimensionality reduction, and missing value imputation. Implements extensions of the original model (Cortes, (2018) ) and can produce different factorizations such as the weighted 'implicit-feedback' model (Hu, Koren, Volinsky, (2008) ), the 'weighted-lambda-regularization' model, (Zhou, Wilkinson, Schreiber, Pan, (2008) ), or the enhanced model with 'implicit features' (Rendle, Zhang, Koren, (2019) ), with or without side information. Can use gradient-based procedures or alternating-least squares procedures (Koren, Bell, Volinsky, (2009) ), with either a Cholesky solver, a faster conjugate gradient solver (Takacs, Pilaszy, Tikk, (2011) ), or a non-negative coordinate descent solver (Franc, Hlavac, Navara, (2005) ), providing efficient methods for sparse and dense data, and mixtures thereof. Supports L1 and L2 regularization in the main models, offers alternative most-popular and content-based models, and implements functionality for cold-start recommendations and imputation of 2D data.
How to cite:
David Cortes (2020). cmfrec: Collective Matrix Factorization for Recommender Systems. R package version 3.5.1-3, https://cran.r-project.org/web/packages/cmfrec. Accessed 04 Jun. 2026.
Previous versions and publish date:
2.3.0 (2020-11-23 10:50), 2.3.2 (2020-11-23 17:30), 2.4.1 (2021-01-06 11:50), 2.4.2 (2021-01-10 16:20), 2.4.5 (2021-03-01 19:40), 3.1.0 (2021-05-20 22:30), 3.1.2 (2021-06-28 06:50), 3.2.1 (2021-07-29 20:50), 3.2.2-1 (2021-09-26 06:30), 3.2.2-2 (2021-11-07 21:10), 3.2.2 (2021-07-30 10:00), 3.3.0 (2022-01-03 14:40), 3.3.1 (2022-01-05 16:50), 3.4.1 (2022-02-10 01:30), 3.4.2 (2022-02-10 15:10), 3.4.3-2 (2022-10-25 19:35), 3.4.3 (2022-07-09 17:50), 3.5.0 (2022-11-26 16:10), 3.5.1-1 (2023-04-11 19:00), 3.5.1-2 (2023-11-28 19:10), 3.5.1 (2023-03-08 23:10)
Other packages that cited cmfrec R package
View cmfrec citation profile
Other R packages that cmfrec depends, imports, suggests or enhances
Complete documentation for cmfrec
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

nextGenShinyApps  
Craft Exceptional 'R Shiny' Applications and Dashboards with Novel Responsive Tools
Nove responsive tools for designing and developing 'Shiny' dashboards and applications. The scripts ...
Download / Learn more Package Citations See dependency  
golem  
A Framework for Robust Shiny Applications
An opinionated framework for building a production-ready 'Shiny' application. This package contains ...
Download / Learn more Package Citations See dependency  
murphydiagram  
Murphy Diagrams for Forecast Comparisons
Data and code for the paper by Ehm, Gneiting, Jordan and Krueger ('Of Quantiles and Expectiles: Con ...
Download / Learn more Package Citations See dependency  
shinybusy  
Busy Indicators and Notifications for 'Shiny' Applications
Add indicators (spinner, progress bar, gif) in your 'shiny' applications to show the user that the ...
Download / Learn more Package Citations See dependency  
AMPLE  
Shiny Apps to Support Capacity Building on Harvest Control Rules
Three Shiny apps are provided that introduce Harvest Control Rules (HCR) for fisheries management. ...
Download / Learn more Package Citations See dependency  
phers  
Calculate Phenotype Risk Scores
Use phenotype risk scores based on linked clinical and genetic data to study Mendelian disease and ...
Download / Learn more Package Citations See dependency  

27,268

R Packages

233,548

Dependencies

72,590

Author Associations

27,205

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA