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spFSR  

Feature Selection and Ranking via Simultaneous Perturbation Stochastic Approximation
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("spFSR", "2.0.4")



Attach the package and use:
library("spFSR")
Maintained by
David Akman
[Scholar Profile | Author Map]
First Published: 2018-05-11
Latest Update: 2023-03-17
Description:
An implementation of feature selection, weighting and ranking via simultaneous perturbation stochastic approximation (SPSA). The SPSA-FSR algorithm searches for a locally optimal set of features that yield the best predictive performance using some error measures such as mean squared error (for regression problems) and accuracy rate (for classification problems).
How to cite:
David Akman (2018). spFSR: Feature Selection and Ranking via Simultaneous Perturbation Stochastic Approximation. R package version 2.0.4, https://cran.r-project.org/web/packages/spFSR. Accessed 20 Apr. 2025.
Previous versions and publish date:
1.0.0 (2018-05-11 15:15), 2.0.1 (2022-10-29 08:22), 2.0.2 (2022-11-08 05:50), 2.0.3 (2022-11-13 10:30)
Other packages that cited spFSR R package
View spFSR citation profile
Other R packages that spFSR depends, imports, suggests or enhances
Complete documentation for spFSR
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