Minimisation of data collection by active learning

Tirthankar Raychaudhuri, Len Hamey

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

16 Citations (Scopus)

Abstract

We use the `query-by-committee' approach for building an active scheme for data collection. In this method data gathering is reduced to a minimum, yet modelling accuracy is uncompromised. Our active querying criterion is determined by whether or not several models agree when they are fitted to random subsamples of a small amount of collected data. Experiments with neural network models to establish the feasibility of our algorithm have produced encouraging results.

Original languageEnglish
Title of host publicationIEEE International Conference on Neural Networks: conference proceedings
Place of PublicationPiscataway, NJ
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages1338-1341
Number of pages4
Volume3
ISBN (Print)0780327683
DOIs
Publication statusPublished - 1995
Event1995 IEEE International Conference on Neural Networks (ICNN 95) - PERTH, Australia
Duration: 27 Nov 19951 Dec 1995

Conference

Conference1995 IEEE International Conference on Neural Networks (ICNN 95)
CountryAustralia
CityPERTH
Period27/11/951/12/95

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Raychaudhuri, T., & Hamey, L. (1995). Minimisation of data collection by active learning. In IEEE International Conference on Neural Networks: conference proceedings (Vol. 3, pp. 1338-1341). Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ICNN.1995.487351