Data Mining on the Sisyphus Dataset: Evaluation and  Integration of Results

T Gartner; Wu Shaomin; PA Flach

Data Mining on the Sisyphus Dataset: Evaluation and Integration of Results

T Gartner
, Wu Shaomin
, PA Flach

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

Abstract

This paper describes our work on the Sisyphus challenge dataset, which includes both classification and clustering tasks. We present our work in the context of the CRISP-DM methodology. Further key aspects of the work are the evaluation and integration of multiple models by means of ROC analysis. We indicate a simple method of forcing classifiers to cover the whole of the ROC space. In conclusion, we outline several promising research directions.

Translated title of the contribution	Data Mining on the Sisyphus Dataset: Evaluation and Integration of Results
Original language	English
Title of host publication	Unknown
Editors	Christophe Giraud-Carrier, Nada Lavrac, Steve Moyle
Publisher	ECML/PKDD'01 workshop notes
Pages	69 - 80
Number of pages	11
Publication status	Published - Sept 2001

Bibliographical note

Conference Proceedings/Title of Journal: Integrating Aspects of Data Mining, Decision Support and Meta-Learning

Access to Document

http://www.cs.bris.ac.uk/Publications/pub_info.jsp?id=1000562

Handle.net

Persistent link

Cite this

@inproceedings{5f5ede0721354ecfa3493f49476ab89d,

title = "Data Mining on the Sisyphus Dataset: Evaluation and Integration of Results",

abstract = "This paper describes our work on the Sisyphus challenge dataset, which includes both classification and clustering tasks. We present our work in the context of the CRISP-DM methodology. Further key aspects of the work are the evaluation and integration of multiple models by means of ROC analysis. We indicate a simple method of forcing classifiers to cover the whole of the ROC space. In conclusion, we outline several promising research directions. ",

author = "T Gartner and Wu Shaomin and PA Flach",

note = "Conference Proceedings/Title of Journal: Integrating Aspects of Data Mining, Decision Support and Meta-Learning",

year = "2001",

month = sep,

language = "English",

pages = "69 -- 80",

editor = "Christophe Giraud-Carrier and Nada Lavrac and Steve Moyle",

booktitle = "Unknown",

publisher = "ECML/PKDD'01 workshop notes",

}

TY - GEN

T1 - Data Mining on the Sisyphus Dataset: Evaluation and Integration of Results

AU - Gartner, T

AU - Shaomin, Wu

AU - Flach, PA

N1 - Conference Proceedings/Title of Journal: Integrating Aspects of Data Mining, Decision Support and Meta-Learning

PY - 2001/9

Y1 - 2001/9

N2 - This paper describes our work on the Sisyphus challenge dataset, which includes both classification and clustering tasks. We present our work in the context of the CRISP-DM methodology. Further key aspects of the work are the evaluation and integration of multiple models by means of ROC analysis. We indicate a simple method of forcing classifiers to cover the whole of the ROC space. In conclusion, we outline several promising research directions.

AB - This paper describes our work on the Sisyphus challenge dataset, which includes both classification and clustering tasks. We present our work in the context of the CRISP-DM methodology. Further key aspects of the work are the evaluation and integration of multiple models by means of ROC analysis. We indicate a simple method of forcing classifiers to cover the whole of the ROC space. In conclusion, we outline several promising research directions.

M3 - Conference Contribution (Conference Proceeding)

SP - 69

EP - 80

BT - Unknown

A2 - Giraud-Carrier, Christophe

A2 - Lavrac, Nada

A2 - Moyle, Steve

PB - ECML/PKDD'01 workshop notes