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Toward a Progress Indicator for Machine Learning Model Building and Data Mining Algorithm Execution

  • ACM SIGKDD Explorations Newsletter
  • Association for Computing Machinery
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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.

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Publication details

DOI
10.1145/3166054.3166057
OpenAlex
W2769845546
Document type
article
Language
EN
Source
ACM SIGKDD Explorations Newsletter
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