Affiliation:
1. University of Washington, Seattle, WA
Abstract
For user-friendliness, many software systems offer progress indicators for long-duration tasks. A typical progress indicator continuously estimates the remaining task execution time as well as the portion of the task that has been finished. Building a machine learning model often takes a long time, but no existing machine learning software supplies a non-trivial progress indicator. Similarly, running a data mining algorithm often takes a long time, but no existing data mining software provides a nontrivial progress indicator. In this article, we consider the problem of offering progress indicators for machine learning model building and data mining algorithm execution. We discuss the goals and challenges intrinsic to this problem. Then we describe an initial framework for implementing such progress indicators and two advanced, potential uses of them, with the goal of inspiring future research on this topic
Publisher
Association for Computing Machinery (ACM)
Reference80 articles.
1. A progress bar for scikit-learn? https://stackoverflow.com/questions/34251980/a-progressbar-for-scikit-learn. A progress bar for scikit-learn? https://stackoverflow.com/questions/34251980/a-progressbar-for-scikit-learn.
2. Aggarwal C.C. Data Mining: The Textbook. New York NY: Springer 2015. Aggarwal C.C. Data Mining: The Textbook. New York NY: Springer 2015.
3. Alpaydin E. Introduction to Machine Learning. Cambridge MA: The MIT Press 2014. Alpaydin E. Introduction to Machine Learning. Cambridge MA: The MIT Press 2014.
4. Babich N. Best practices for animated progress indicators. https://www.smashingmagazine.com/2016/12/best-practicesfor-animated-progress-indicators/. Babich N. Best practices for animated progress indicators. https://www.smashingmagazine.com/2016/12/best-practicesfor-animated-progress-indicators/.
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