Random Forest Classifier executed in 3 nodes, 1 master and 2 workers, with a generated dataset, using 1 Million rows x 100 features Version 1
Download RO-CrateName: Random Forest
Contact Person: [email protected]
Access Level: public
License Agreement: Apache2
Platform: COMPSs
Machine: MareNostrum4
This is an example of Random Forest algorithm from dislib. To show the usage, the code generates a synthetical input matrix.
The results are printed by screen.
This application used dislib-0.9.0
Click and drag the diagram to pan, double click or use the controls to zoom.
Version History
Version 1 (earliest) Created 14th Feb 2024 at 14:05 by Fernando Vázquez-Novoa
Frozen
Version-1c310c2c
Creators and Submitter
Views: 1132 Downloads: 265
Created: 14th Feb 2024 at 14:05
Last updated: 9th Aug 2024 at 08:14
Tags AttributionsNone
Related items
https://orcid.org/0000-0001-5634-509X
eFlows4HPC project aims at providing workflow software stack and an additional set of services to enable the integration of HPC simulations and modelling with big data analytics and machine learning in scientific and industrial applications. The project is also developing the HPC Workflows as a Service (HPCWaaS) methodology that aims at providing tools to simplify the development, deployment, execution and reuse of workflows. The project demonstrates its advances through three application Pillars ...
Teams: Cluster Emergent del Cervell Humà, Workflows and Distributed Computing, Pillar I: Manufacturing, Pillar II: Climate, Pillar III: Urgent computing for natural hazards, eFlows4HPC general, COMPSs Tutorials
Web page: https://eflows4hpc.eu
This team is to publish workflows executed from WPs that are not the three main pillars of the project.
Space: eFlows4HPC
Public web page: https://eflows4hpc.eu/
Distributed computing aims to offer tools and mechanisms that enable the sharing, selection, and aggregation of a wide variety of geographically distributed computational resources in a transparent way. The research done in this team is based on the past expertise of the group, and on extending it towards the aspects of distributed computing that can benefit from this expertise. The team at BSC has a strong focus on programming models and resource management and scheduling in distributed computing ...
