A new paper explores how visual analytics (VA) can be used to inject human knowledge into machine learning (ML) workflows. Researchers surveyed over 200 VIS4ML papers, analyzing them from perspectives of ML characteristics, visualization, interaction, and actions. The findings provide evidence for the benefits of using VA in ML processes, offering pathways for transferring human expertise to ML workflows through interactive visualization. AI
IMPACT This research highlights methods for improving machine learning workflows by integrating human expertise through visual tools.
RANK_REASON The cluster contains a research paper detailing a survey and analysis of existing literature on a specific topic within machine learning. [lever_c_demoted from research: ic=1 ai=1.0]
- alphaXiv
- arXiv
- CatalyzeX
- CORE Recommender
- DagsHub
- Gotit.pub
- Hugging Face
- IEEE Visualization
- Influence Flower
- machine learning
- ScienceCast
- VIS4ML: An Ontology for Visual Analytics Assisted Machine Learning
- visual analytics
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