Package: recosystem 0.5.1
recosystem: Recommender System using Matrix Factorization
R wrapper of the 'libmf' library <https://www.csie.ntu.edu.tw/~cjlin/libmf/> for recommender system using matrix factorization. It is typically used to approximate an incomplete matrix using the product of two matrices in a latent space. Other common names for this task include "collaborative filtering", "matrix completion", "matrix recovery", etc. High performance multi-core parallel computing is supported in this package.
Authors:
recosystem_0.5.1.tar.gz
recosystem_0.5.1.tar.gz(r-4.5-noble)recosystem_0.5.1.tar.gz(r-4.4-noble)
recosystem_0.5.1.tgz(r-4.4-emscripten)recosystem_0.5.1.tgz(r-4.3-emscripten)
recosystem.pdf |recosystem.html✨
recosystem/json (API)
NEWS
# Install 'recosystem' in R: |
install.packages('recosystem', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/yixuan/recosystem/issues
Last updated 2 years agofrom:47326c505f. Checks:OK: 2. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 10 2024 |
R-4.5-linux-x86_64 | OK | Nov 10 2024 |
Exports:data_filedata_matrixdata_memoryout_fileout_memoryout_nothingReco
Dependencies:floatRcppRcppProgress
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Specifying Data Source | data_file data_matrix data_memory data_source |
Exporting Factorization Matrices | output |
Specifying Output Format | output_format out_file out_memory out_nothing |
Recommender Model Predictions | predict |
Constructing a Recommender System Object | Reco |
Training a Recommender Model | train |
Tuning Model Parameters | tune |