Posit Package Manager vs Weka
Posit Package Manager
posit.coWeka
weka.waikato.ac.nzSide by side
| Figure | Posit Package Manager | Weka |
|---|---|---|
| Price from | — | Free |
| Free plan | — | Yes |
| Free trial | Yes | — |
| Open source | — | Yes |
| Web | Yes | — |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 2 | 3 |
| Spec score · Data Science Analytics | 7.7 (#17) | 8.2 (#9) |
| Headquarters | Boston, Massachusetts, United States | Hamilton, New Zealand |
| Purpose | Posit Package Manager centralizes and governs R and Python package repositories for organizations. | Weka is open-source machine learning software issued under the GNU General Public License. |
| Support channels | email, ticket, community, docs | The project directs users to mailing-list archives, help forums, bug reporting and an IRC channel. |
Plans
Posit Package Manager
- AdvancedPriced on request
- EnhancedPriced on request
In their own words
Posit Package Manager
Posit Package Manager has no write-up on Specifiction yet; its figures are above.
Weka
Weka is open-source machine-learning software for building and evaluating models, with support for forecasting and time-series modeling. It is available free under the GNU General Public License, with Weka 3.8 as the stable release and 3.9 as the development version. The stable branch receives fixes and feature updates intended to preserve compatibility; development builds may introduce breaking changes. Weka provides a Java API, Javadoc for its API and command-line parameters, and can also be used through Jupyter notebooks. Official releases require Java 8 or later. Downloads are listed for Windows, Mac OS, and Linux, with Intel and ARM options. Both branches include a package manager for community extensions, though installing packages requires internet access. The software includes built-in help and a comprehensive manual, with additional assistance through documentation, mailing list archives, forums, and a mailing list. Distributed derivative works must use the GPL; commercial projects needing Weka code in a non-GPL program may be able to obtain a suitable license. Models serialized in version 3.7 are incompatible with 3.8, and the migrator has an exception for RandomForest.