The Role of Visualization in Machine Learning
Problem
Visual Analytics is a process supporting the information discovery through a combination of automated analysis methods, interactive visual interfaces, human perception, and reasoning. It is an effective solution to make sense of the data. A possible automatic analysis method is Machine Learning.
Aim
You should provide a systematic overview of existing approaches in scientific literature that use visualization in selected Machine Learning approaches.
Other information
Starting point(s) for research:
Endert, A., Ribarsky, W., Turkay, C., Wong, B.L.W., Nabney, I.T., Diaz-Blanco, I. and Rossi, F. The State of the Art in Integrating Machine Learning into Visual Analytics. Computer Graphics Forum, 36(8):458–486, 2017. doi:10.1111/cgf.13092.
Chatzimparmpas, A., Martins, R. M., Jusufi, I., & Kerren, A. A Survey of Surveys on the Use of Visualization for Interpreting Machine Learning Models. Information Visualization, 19(3), 207-233, 2020. doi: 10.1177/1473871620904671.
Wang, Q., Chen, Z. , Wang, Y., and Qu, H. A Survey on ML4VIS: Applying Machine Learning Advances to Data Visualization, IEEE Transactions on Visualization & Computer Graphics, 28(12):5134-5153, 2022. doi: 10.1109/TVCG.2021.3106142.
T. Spinner, U. Schlegel, H. Schäfer and M. El-Assady, explAIner: A Visual Analytics Framework for Interactive and Explainable Machine Learning, IEEE Transactions on Visualization and Computer Graphics, 26(1):1064-1074, 2020, doi: 10.1109/TVCG.2019.2934629.
Ono, J.P., Castelo, S., Lopez, R., Bertini, E., Freire, J., and Silva, C. PipelineProfiler: A Visual Analytics Tool for the Exploration of AutoML Pipelines, IEEE Transactions on Visualization & Computer Graphics, 27(02): 390-400, 2021. doi 10.1109/TVCG.2020.3030361.