{"title":"机器学习模型构建和数据挖掘算法执行的进展指标:立场文件。","authors":"Gang Luo","doi":"10.1145/3166054.3166057","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":90050,"journal":{"name":"SIGKDD explorations : newsletter of the Special Interest Group (SIG) on Knowledge Discovery & Data Mining","volume":"19 2","pages":"13-24"},"PeriodicalIF":0.0000,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3166054.3166057","citationCount":"16","resultStr":"{\"title\":\"Toward a Progress Indicator for Machine Learning Model Building and Data Mining Algorithm Execution: A Position Paper.\",\"authors\":\"Gang Luo\",\"doi\":\"10.1145/3166054.3166057\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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.</p>\",\"PeriodicalId\":90050,\"journal\":{\"name\":\"SIGKDD explorations : newsletter of the Special Interest Group (SIG) on Knowledge Discovery & Data Mining\",\"volume\":\"19 2\",\"pages\":\"13-24\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1145/3166054.3166057\",\"citationCount\":\"16\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SIGKDD explorations : newsletter of the Special Interest Group (SIG) on Knowledge Discovery & Data Mining\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3166054.3166057\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"SIGKDD explorations : newsletter of the Special Interest Group (SIG) on Knowledge Discovery & Data Mining","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3166054.3166057","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Toward a Progress Indicator for Machine Learning Model Building and Data Mining Algorithm Execution: A Position Paper.
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.