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AutoAIViz
- Source :
- IUI
- Publication Year :
- 2020
- Publisher :
- ACM, 2020.
-
Abstract
- Artificial Intelligence (AI) can now automate the algorithm selection, feature engineering, and hyperparameter tuning steps in a machine learning workflow. Commonly known as AutoML or AutoAI, these technologies aim to relieve data scientists from the tedious manual work. However, today's AutoAI systems often present only limited to no information about the process of how they select and generate model results. Thus, users often do not understand the process, neither do they trust the outputs. In this short paper, we provide a first user evaluation by 10 data scientists of an experimental system, AutoAIViz, that aims to visualize AutoAI's model generation process. We find that the proposed system helps users to complete the data science tasks, and increases their understanding, toward the goal of increasing trust in the AutoAI system.<br />Comment: 5 pages, 1 figure, IUI2020
- Subjects :
- FOS: Computer and information sciences
Feature engineering
Hyperparameter
Computer Science - Machine Learning
Process (engineering)
Computer science
business.industry
05 social sciences
Short paper
Computer Science - Human-Computer Interaction
Machine Learning (stat.ML)
020207 software engineering
02 engineering and technology
Machine Learning (cs.LG)
Human-Computer Interaction (cs.HC)
Visualization
Workflow
Experimental system
Statistics - Machine Learning
0202 electrical engineering, electronic engineering, information engineering
0501 psychology and cognitive sciences
Artificial intelligence
business
050107 human factors
Parallel coordinates
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- Proceedings of the 25th International Conference on Intelligent User Interfaces
- Accession number :
- edsair.doi.dedup.....d2d56ae9e030e3a06e42c98f179f351b