SSLR
Semi-Supervised Classification, Regression and Clustering Methods
Providing a collection of techniques for semi-supervised classification, regression and clustering. In semi-supervised problem, both labeled and unlabeled data are used to train a classifier. The package includes a collection of semi-supervised learning techniques: self-training, co-training, democratic, decision tree, random forest, 'S3VM' ... etc, with a fairly intuitive interface that is easy to use.
- Version0.9.3.3
- R version≥ 2.10
- LicenseGPL-3
- Needs compilation?Yes
- Last release07/22/2021
Documentation
Team
Francisco Jesús Palomares Alabarce
Christoph Bergmeir
Show author detailsRolesContributorJosé Manuel Benítez
Isaac Triguero
Mabel González
Insights
Last 30 days
This package has been downloaded 259 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 10 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 3,109 times in the last 365 days. That's enough downloads to impress a room full of undergrads. A commendable achievement indeed. The day with the most downloads was Sep 11, 2024 with 42 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
Binaries
Dependencies
- Imports12 packages
- Suggests18 packages
- Linking To2 packages