https://store-images.s-microsoft.com/image/apps.39362.347eb4b3-de69-4ef3-a05e-52f3970834ca.54ab4359-8377-4219-a69e-9d1a17bf07d2.d467e061-9f22-4ede-83bd-09f7ed20e455

Weka Machine Learning Software on Windows Server 2016

AskforCloud LLC

Kategóriák
Mesterséges intelligencia és gépi tanulásIT és felügyeleti eszközökSzámítás
Támogatás
Támogatás
Jogi tudnivalók
Standard Microsoft-szerződés alapjánAdatvédelmi szabályzat

Weka Machine Learning Software on Windows Server 2016

AskforCloud LLC

Weka is a collection of machine learning algorithms for data mining tasks.

Weka is an open source software issued under the GNU General Public License.Weka is a collection of machine learning algorithms for data mining tasks.

Weka supports several standard data mining tasks, more specifically, data preprocessing, clustering, classification, regression, visualization, and feature selection.

Version - 3.8.6

Ports:
🗸 Windows (RDP) : 3389 TCP

Advantages:

🗸Free availability under the GNU General Public License.
🗸Portability, since it is fully implemented in the Java programming language and thus runs on almost any modern computing platform.
🗸A comprehensive collection of data preprocessing and modeling techniques.
🗸Ease of use due to its graphical user interfaces.

Disclaimer : This Virtual machine offer contains free and open source software. All the softwares, trademarks used in the Virtual machine offer are the exclusive property of their respective owners. Askforcloud LLC does not offer commercial license of the product mentioned above.

Note :

🗸 Waikato Environment for Knowledge Analysis (Weka), developed at the University of Waikato, New Zealand, is free software licensed under the GNU General Public License.
További információ
Weka Machine Learning Software Documentation
https://store-images.s-microsoft.com/image/apps.19324.347eb4b3-de69-4ef3-a05e-52f3970834ca.54ab4359-8377-4219-a69e-9d1a17bf07d2.2324779d-4c7a-4b51-90fd-23161efc5142
https://store-images.s-microsoft.com/image/apps.19324.347eb4b3-de69-4ef3-a05e-52f3970834ca.54ab4359-8377-4219-a69e-9d1a17bf07d2.2324779d-4c7a-4b51-90fd-23161efc5142