Other packages > Find by keyword >

rsparse  

Statistical Learning on Sparse Matrices
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("rsparse", "0.5.2")



Attach the package and use:
library("rsparse")
Maintained by
Dmitriy Selivanov
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-04-12
Latest Update: 2022-09-11
Description:
Implements many algorithms for statistical learning on sparse matrices - matrix factorizations, matrix completion, elastic net regressions, factorization machines. Also 'rsparse' enhances 'Matrix' package by providing methods for multithreaded matrix products and native slicing of the sparse matrices in Compressed Sparse Row (CSR) format. List of the algorithms for regression problems: 1) Elastic Net regression via Follow The Proximally-Regularized Leader (FTRL) Stochastic Gradient Descent (SGD), as per McMahan et al(, ) 2) Factorization Machines via SGD, as per Rendle (2010, ) List of algorithms for matrix factorization and matrix completion: 1) Weighted Regularized Matrix Factorization (WRMF) via Alternating Least Squares (ALS) - paper by Hu, Koren, Volinsky (2008, ) 2) Maximum-Margin Matrix Factorization via ALS, paper by Rennie, Srebro (2005, ) 3) Fast Truncated Singular Value Decomposition (SVD), Soft-Thresholded SVD, Soft-Impute matrix completion via ALS - paper by Hastie, Mazumder et al. (2014, ) 4) Linear-Flow matrix factorization, from 'Practical linear models for large-scale one-class collaborative filtering' by Sedhain, Bui, Kawale et al (2016, ISBN:978-1-57735-770-4) 5) GlobalVectors (GloVe) matrix factorization via SGD, paper by Pennington, Socher, Manning (2014, ) Package is reasonably fast and memory efficient - it allows to work with large datasets - millions of rows and millions of columns. This is particularly useful for practitioners working on recommender systems.
How to cite:
Dmitriy Selivanov (2019). rsparse: Statistical Learning on Sparse Matrices. R package version 0.5.2, https://cran.r-project.org/web/packages/rsparse. Accessed 03 Dec. 2024.
Previous versions and publish date:
0.3.3.1 (2019-04-14 22:13), 0.3.3.2 (2019-07-18 15:30), 0.3.3.3 (2019-08-04 12:00), 0.3.3.4 (2019-11-14 13:30), 0.3.3 (2019-04-12 10:42), 0.4.0 (2020-04-01 19:50), 0.5.0 (2021-11-30 08:50), 0.5.1 (2022-09-12 00:20)
Other packages that cited rsparse R package
View rsparse citation profile
Other R packages that rsparse depends, imports, suggests or enhances
Complete documentation for rsparse
Downloads during the last 30 days
Get rewarded with contribution points by helping add
Reviews / comments / questions /suggestions ↴↴↴

Today's Hot Picks in Authors and Packages

telemac  
R Interface to the TELEMAC Model Suite
An R interface to the TELEMAC suite for modelling of free surface flow. This includes methods for m ...
Download / Learn more Package Citations See dependency  
FSInteract  
Fast Searches for Interactions
Performs fast detection of interactions in large-scale data using the method of random intersection ...
Download / Learn more Package Citations See dependency  
r2resize  
In-Text Resize for Images, Tables and Fancy Resize Containers in 'shiny', 'rmarkdown' and 'quarto' Documents
Automatic resizing toolbar for containers, images and tables. Various resizable or expandable contai ...
Download / Learn more Package Citations See dependency  
CRANsearcher  
RStudio Addin for Searching Packages in CRAN Database Based on Keywords
One of the strengths of R is its vast package ecosystem. Indeed, R packages extend from visualizatio ...
Download / Learn more Package Citations See dependency  
EDOtrans  
Euclidean Distance-Optimized Data Transformation
A data transformation method which takes into account the special property of scale non-invariance w ...
Download / Learn more Package Citations See dependency  
donut  
Nearest Neighbour Search with Variables on a Torus
Finds the k nearest neighbours in a dataset of specified points, adding the option to wrap certain ...
Download / Learn more Package Citations See dependency  

23,310

R Packages

200,798

Dependencies

63,203

Author Associations

23,278

Publication Badges

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