| Literature DB >> 29177022 |
Gang Luo1.
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.Entities:
Keywords: Machine learning; automatic administration; data mining; load management; progress indicator
Year: 2017 PMID: 29177022 PMCID: PMC5699516 DOI: 10.1145/3166054.3166057
Source DB: PubMed Journal: SIGKDD Explor ISSN: 1931-0145