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R-rsparse rpm build for : OpenSuSE. For other distributions click R-rsparse.

Name : R-rsparse
Version : 0.5.2 Vendor : obs://build_opensuse_org/devel:languages:R
Release : lp156.1.4 Date : 2024-09-12 10:45:30
Group : Development/Libraries/Other Source RPM : R-rsparse-0.5.2-lp156.1.4.src.rpm
Size : 1.34 MB
Packager : https://www_suse_com/
Summary : Statistical Learning on Sparse Matrices
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 < sparse, dense> 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(,
< doi:10.1145/2487575.2488200>) 2) Factorization Machines via SGD, as
per Rendle (2010, < doi:10.1109/ICDM.2010.127>) 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, < doi:10.1109/ICDM.2008.22>) 2)
Maximum-Margin Matrix Factorization via ALS, paper by Rennie, Srebro
(2005, < doi:10.1145/1102351.1102441>) 3) Fast Truncated Singular Value
Decomposition (SVD), Soft-Thresholded SVD, Soft-Impute matrix
completion via ALS - paper by Hastie, Mazumder et al. (2014,
< doi:10.48550/arXiv.1410.2596>) 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,
< https://aclanthology.org/D14-1162/>) 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.

RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/15.6/x86_64

Content of RPM  Provides Requires

Download
ftp.icm.edu.pl  R-rsparse-0.5.2-lp156.1.4.x86_64.rpm
     

Provides :
R-rsparse
R-rsparse(x86-64)

Requires :
R-MatrixExtra
R-R6
R-Rcpp
R-RcppArmadillo
R-RhpcBLASctl
R-base
R-data.table
R-float
R-lgr
ld-linux-x86-64.so.2()(64bit)
ld-linux-x86-64.so.2(GLIBC_2.3)(64bit)
libR.so()(64bit)
libRblas.so()(64bit)
libRlapack.so()(64bit)
libc.so.6()(64bit)
libc.so.6(GLIBC_2.11)(64bit)
libc.so.6(GLIBC_2.14)(64bit)
libc.so.6(GLIBC_2.2.5)(64bit)
libc.so.6(GLIBC_2.3.4)(64bit)
libc.so.6(GLIBC_2.4)(64bit)
libgcc_s.so.1()(64bit)
libgcc_s.so.1(GCC_3.0)(64bit)
libgomp.so.1()(64bit)
libgomp.so.1(GOMP_1.0)(64bit)
libgomp.so.1(GOMP_2.0)(64bit)
libgomp.so.1(GOMP_4.0)(64bit)
libgomp.so.1(OMP_1.0)(64bit)
libm.so.6()(64bit)
libm.so.6(GLIBC_2.2.5)(64bit)
libm.so.6(GLIBC_2.27)(64bit)
libm.so.6(GLIBC_2.29)(64bit)
libstdc++.so.6()(64bit)
libstdc++.so.6(CXXABI_1.3)(64bit)
libstdc++.so.6(CXXABI_1.3.9)(64bit)
libstdc++.so.6(GLIBCXX_3.4)(64bit)
libstdc++.so.6(GLIBCXX_3.4.11)(64bit)
libstdc++.so.6(GLIBCXX_3.4.18)(64bit)
libstdc++.so.6(GLIBCXX_3.4.20)(64bit)
libstdc++.so.6(GLIBCXX_3.4.21)(64bit)
libstdc++.so.6(GLIBCXX_3.4.9)(64bit)
rpmlib(CompressedFileNames) <= 3.0.4-1
rpmlib(FileDigests) <= 4.6.0-1
rpmlib(PayloadFilesHavePrefix) <= 4.0-1
rpmlib(PayloadIsXz) <= 5.2-1


Content of RPM :
/usr/lib64/R/library/rsparse
/usr/lib64/R/library/rsparse/DESCRIPTION
/usr/lib64/R/library/rsparse/INDEX
/usr/lib64/R/library/rsparse/Meta
/usr/lib64/R/library/rsparse/Meta/Rd.rds
/usr/lib64/R/library/rsparse/Meta/data.rds
/usr/lib64/R/library/rsparse/Meta/features.rds
/usr/lib64/R/library/rsparse/Meta/hsearch.rds
/usr/lib64/R/library/rsparse/Meta/links.rds
/usr/lib64/R/library/rsparse/Meta/nsInfo.rds
/usr/lib64/R/library/rsparse/Meta/package.rds
/usr/lib64/R/library/rsparse/NAMESPACE
/usr/lib64/R/library/rsparse/NEWS.md
/usr/lib64/R/library/rsparse/R
/usr/lib64/R/library/rsparse/R/rsparse
/usr/lib64/R/library/rsparse/R/rsparse.rdb
/usr/lib64/R/library/rsparse/R/rsparse.rdx
/usr/lib64/R/library/rsparse/data
/usr/lib64/R/library/rsparse/data/Rdata.rdb
/usr/lib64/R/library/rsparse/data/Rdata.rds
/usr/lib64/R/library/rsparse/data/Rdata.rdx
/usr/lib64/R/library/rsparse/help
/usr/lib64/R/library/rsparse/help/AnIndex
/usr/lib64/R/library/rsparse/help/aliases.rds
/usr/lib64/R/library/rsparse/help/figures
/usr/lib64/R/library/rsparse/help/figures/logo.png
/usr/lib64/R/library/rsparse/help/paths.rds
/usr/lib64/R/library/rsparse/help/rsparse.rdb
/usr/lib64/R/library/rsparse/help/rsparse.rdx
/usr/lib64/R/library/rsparse/html
There is 12 files more in these RPM.

 
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