The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
The genetic algorithm can be used directly to find the similarity of users and more effectively to increase the efficiency of the collaborative filtering method. By identifying the nearest neighbors to the active user, before the genetic algorithm, and by identifying suitable starting points, an effective method for user-based collaborative filtering method has been developed. This package uses an optimization algorithm (continuous genetic algorithm) to directly find the optimal similarities between active users (users for whom current recommendations are made) and others. First, by determining the nearest neighbor and their number, the number of genes in a chromosome is determined. Each gene represents the neighbor's similarity to the active user. By estimating the starting points of the genetic algorithm, it quickly converges to the optimal solutions. The positive point is the independence of the genetic algorithm on the number of data that for big data is an effective help in solving the problem.
| Version: | 1.0 |
| Depends: | R (≥ 3.0.0), graphics, stats, utils |
| Published: | 2019-12-20 |
| DOI: | 10.32614/CRAN.package.GACFF |
| Author: | Farimah Houshmand Nanehkaran, Seyed Mohammad Reza Lajevardi, Mahmoud Mahlouji Bidgholi |
| Maintainer: | Farimah Houshmand Nanehkaran <hoshmandcomputer at gmail.com> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| CRAN checks: | GACFF results |
| Reference manual: | GACFF.pdf |
| Package source: | GACFF_1.0.tar.gz |
| Windows binaries: | r-devel: GACFF_1.0.zip, r-release: GACFF_1.0.zip, r-oldrel: GACFF_1.0.zip |
| macOS binaries: | r-release (arm64): GACFF_1.0.tgz, r-oldrel (arm64): GACFF_1.0.tgz, r-release (x86_64): GACFF_1.0.tgz, r-oldrel (x86_64): GACFF_1.0.tgz |
Please use the canonical form https://CRAN.R-project.org/package=GACFF to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.