A Meta-learning Approach to Improve Progressive Sampling

Rui Leite; Pavel Brazdil

Research.Publish.Connect.

*Please fill out at least one Field. *Value must be an number!

Title:
ISBN:
Year:
Acronym:
Subject:

Advanced Search Proceedings Search

If you're looking for an exact phrase use quotation marks on text fields.

*Please fill out at least one Field.

Title:
Author:
Affiliation:
Subject:

Advanced Search Papers Search

If you're looking for an exact phrase use quotation marks on text fields.

*Please fill out at least one Field.

Name:
Affiliation:
Country:
Conference:
Subject:

Advanced Search Authors Search

If you're looking for an exact phrase use quotation marks on text fields.

*Please fill out at least one Field.

Name:
Country:
Subject:

Advanced Search Affiliations Search

If you're looking for an exact phrase use quotation marks on text fields.

Proceedings

Proceedings Search *Please fill out at least one Field. *Value must be an number!

Title:
ISBN:
Year:
Acronym:
Subject:

Advanced Search Proceedings Search

If you're looking for an exact phrase use quotation marks on text fields.

Papers

Papers Search *Please fill out at least one Field.

Title:
Author:
Affiliation:
Subject:

Advanced Search Papers Search

If you're looking for an exact phrase use quotation marks on text fields.

Authors

Authors Search *Please fill out at least one Field.

Name:
Affiliation:
Country:
Conference:
Subject:

Advanced Search Authors Search

If you're looking for an exact phrase use quotation marks on text fields.

Advanced Search

Paper

A Meta-learning Approach to Improve Progressive Sampling

In Proceedings of the 4th International Workshop on Pattern Recognition in Information Systems - Volume 0ICEIS, 25-34, 2004 , Porto, Portugal

Authors: Rui Leite and Pavel Brazdil

Affiliation: LIACC/FEP, University of Porto, Portugal

Abstract: We present a method that can be seen as an improvement of standard progressive sampling method. The method exploits information concerning performance of a given algorithm on past datasets, which is used to generate predictions of the stopping point. Experimental evaluation shows that the method can lead to significant time savings without significant losses in accuracy.

CC BY-NC-ND 4.0

Guest: Register as new SciTePress user now for free.

SciTePress user: please login.

My Papers

You are not signed in, therefore limits apply to your IP address 18.224.59.138

In the current month:

Recent papers: 100 available of 100 total

2⁺ years older papers: 200 available of 200 total

Paper citation in several formats:

Leite, R. and Brazdil, P. (2004). A Meta-learning Approach to Improve Progressive Sampling. In Proceedings of the 4th International Workshop on Pattern Recognition in Information Systems (ICEIS 2004) - PRIS; ISBN 972-8865-01-5, SciTePress, pages 25-34. DOI: 10.5220/0002668800250034

@conference{pris04,
author={Rui Leite. and Pavel Brazdil.},
title={A Meta-learning Approach to Improve Progressive Sampling},
booktitle={Proceedings of the 4th International Workshop on Pattern Recognition in Information Systems (ICEIS 2004) - PRIS},
year={2004},
pages={25-34},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002668800250034},
isbn={972-8865-01-5},
}

TY - CONF

JO - Proceedings of the 4th International Workshop on Pattern Recognition in Information Systems (ICEIS 2004) - PRIS
TI - A Meta-learning Approach to Improve Progressive Sampling
SN - 972-8865-01-5
AU - Leite, R.
AU - Brazdil, P.
PY - 2004
SP - 25
EP - 34
DO - 10.5220/0002668800250034
PB - SciTePress