Accurate modelling with minimised data collection - an active learning algorithm

Tirthankar Raychaudhuri; Leonard Hamey

Accurate modelling with minimised data collection - an active learning algorithm

Tirthankar Raychaudhuri, Leonard Hamey

School of Computing

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

Abstract

A data gathering method based on active querying is described. In this method data is reduced to a minimum, yet modelling accuracy is uncompromised. Our active querying criterion is determined by whether or not several neural network models agree when they are fitted to random subsamples of a small amount of collected data. Experiments have established the feasibility of our algorithm. It is also shown that our approach results in a more samples being collected in the neighbourhood of the more significant inputs.

Original language	English
Title of host publication	Proceedings of the Seventh Australian Conference on Neural Networks
Editors	Peter Bartlett, Anthony Burkitt, Robert C. Williamson
Place of Publication	Canberra
Publisher	ANU
Pages	11-15
Number of pages	5
ISBN (Print)	0731524292
Publication status	Published - 1996
Event	Australian Conference on Neural Networks (7th : 1996) - Canberra, Australia Duration: 10 Apr 1996 → 12 Apr 1996

Conference

Conference	Australian Conference on Neural Networks (7th : 1996)
Country/Territory	Australia
City	Canberra
Period	10/04/96 → 12/04/96

Cite this

@inproceedings{b76067e0604d4c65992a5bf66d1163d3,

title = "Accurate modelling with minimised data collection - an active learning algorithm",

abstract = "A data gathering method based on active querying is described. In this method data is reduced to a minimum, yet modelling accuracy is uncompromised. Our active querying criterion is determined by whether or not several neural network models agree when they are fitted to random subsamples of a small amount of collected data. Experiments have established the feasibility of our algorithm. It is also shown that our approach results in a more samples being collected in the neighbourhood of the more significant inputs.",

author = "Tirthankar Raychaudhuri and Leonard Hamey",

year = "1996",

language = "English",

isbn = "0731524292",

pages = "11--15",

editor = "Peter Bartlett and Anthony Burkitt and Williamson, {Robert C.}",

booktitle = "Proceedings of the Seventh Australian Conference on Neural Networks",

publisher = "ANU",

note = "Australian Conference on Neural Networks (7th : 1996) ; Conference date: 10-04-1996 Through 12-04-1996",

}

Accurate modelling with minimised data collection - an active learning algorithm. / Raychaudhuri, Tirthankar; Hamey, Leonard.

Proceedings of the Seventh Australian Conference on Neural Networks. ed. / Peter Bartlett; Anthony Burkitt; Robert C. Williamson. Canberra : ANU, 1996. p. 11-15.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

TY - GEN

T1 - Accurate modelling with minimised data collection - an active learning algorithm

AU - Raychaudhuri, Tirthankar

AU - Hamey, Leonard

PY - 1996

Y1 - 1996

N2 - A data gathering method based on active querying is described. In this method data is reduced to a minimum, yet modelling accuracy is uncompromised. Our active querying criterion is determined by whether or not several neural network models agree when they are fitted to random subsamples of a small amount of collected data. Experiments have established the feasibility of our algorithm. It is also shown that our approach results in a more samples being collected in the neighbourhood of the more significant inputs.

AB - A data gathering method based on active querying is described. In this method data is reduced to a minimum, yet modelling accuracy is uncompromised. Our active querying criterion is determined by whether or not several neural network models agree when they are fitted to random subsamples of a small amount of collected data. Experiments have established the feasibility of our algorithm. It is also shown that our approach results in a more samples being collected in the neighbourhood of the more significant inputs.

M3 - Conference proceeding contribution

SN - 0731524292

SP - 11

EP - 15

BT - Proceedings of the Seventh Australian Conference on Neural Networks

A2 - Bartlett, Peter

A2 - Burkitt, Anthony

A2 - Williamson, Robert C.

PB - ANU

CY - Canberra

T2 - Australian Conference on Neural Networks (7th : 1996)

Y2 - 10 April 1996 through 12 April 1996

ER -

Accurate modelling with minimised data collection - an active learning algorithm

Abstract

Conference

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