Literature DB >> 30854154

Progress Indication for Machine Learning Model Building: A Feasibility Demonstration.

Gang Luo1.   

Abstract

Progress indicators are desirable for machine learning model building that often takes a long time, by continuously estimating the remaining model building time and the portion of model building work that has been finished. Recently, we proposed a high-level framework using system approaches to support non-trivial progress indicators for machine learning model building, but offered no detailed implementation technique. It remains to be seen whether it is feasible to provide such progress indicators. In this paper, we fill this gap and give the first demonstration that offering such progress indicators is viable. We describe detailed progress indicator implementation techniques for three major, supervised machine learning algorithms. We report an implementation of these techniques in Weka.

Entities:  

Keywords:  Machine learning; Weka; progress indicator

Year:  2018        PMID: 30854154      PMCID: PMC6402496          DOI: 10.1145/3299986.3299988

Source DB:  PubMed          Journal:  SIGKDD Explor        ISSN: 1931-0145


  3 in total

1.  Toward a Progress Indicator for Machine Learning Model Building and Data Mining Algorithm Execution: A Position Paper.

Authors:  Gang Luo
Journal:  SIGKDD Explor       Date:  2017-12

2.  PredicT-ML: a tool for automating machine learning model building with big clinical data.

Authors:  Gang Luo
Journal:  Health Inf Sci Syst       Date:  2016-06-08

3.  Automating Construction of Machine Learning Models With Clinical Big Data: Proposal Rationale and Methods.

Authors:  Gang Luo; Bryan L Stone; Michael D Johnson; Peter Tarczy-Hornoch; Adam B Wilcox; Sean D Mooney; Xiaoming Sheng; Peter J Haug; Flory L Nkoy
Journal:  JMIR Res Protoc       Date:  2017-08-29
  3 in total
  3 in total

1.  Progress Indication for Deep Learning Model Training: A Feasibility Demonstration.

Authors:  Qifei Dong; Gang Luo
Journal:  IEEE Access       Date:  2020-04-22       Impact factor: 3.367

2.  Improving the Accuracy of Progress Indication for Constructing Deep Learning Models.

Authors:  Qifei Dong; Xiaoyi Zhang; Gang Luo
Journal:  IEEE Access       Date:  2022-06-08       Impact factor: 3.476

Review 3.  An Improved Transition Probability Matrix for Crime Distribution Prediction.

Authors:  Junhao Zhang; Kaicun Zhang; Weiping Li
Journal:  Comput Intell Neurosci       Date:  2022-08-10
  3 in total

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