Analyzing feature significance from various systems for mass diagnosis

Ping Zhang; Kuldeep Kumar

doi:10.1109/CIMCA.2006.46

Analyzing feature significance from various systems for mass diagnosis

Ping Zhang^*
, Kuldeep Kumar

^*Corresponding author for this work

Bond Business School

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

4 Citations (Scopus)

Abstract

This paper compares a few classification models for mass classification and analyzes the feature significance for mass classification using various models. It involves a few algorithms for feature selection and also analyzes the individual feature significance. The comparison of classification models is based on the same dataseis for mass diagnosis.

Original language	English
Title of host publication	CIMCA 2006: International Conference on Computational Intelligence for Modelling, Control and Automation, Jointly with IAWTIC 2006: International Conference on Intelligent Agents Web Technologies ...
DOIs	https://doi.org/10.1109/CIMCA.2006.46
Publication status	Published - 2007
Event	CIMCA 2006: International Conference on Computational Intelligence for Modelling, Control and Automation, Jointly with IAWTIC 2006: International Conference on Intelligent Agents Web Technologies and International Commerce - Sydney, NSW, Australia Duration: 28 Nov 2006 → 1 Dec 2006

Conference

Conference	CIMCA 2006: International Conference on Computational Intelligence for Modelling, Control and Automation, Jointly with IAWTIC 2006: International Conference on Intelligent Agents Web Technologies and International Commerce
Country/Territory	Australia
City	Sydney, NSW
Period	28/11/06 → 1/12/06

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10.1109/CIMCA.2006.46

Cite this

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title = "Analyzing feature significance from various systems for mass diagnosis",

abstract = "This paper compares a few classification models for mass classification and analyzes the feature significance for mass classification using various models. It involves a few algorithms for feature selection and also analyzes the individual feature significance. The comparison of classification models is based on the same dataseis for mass diagnosis.",

author = "Ping Zhang and Kuldeep Kumar",

year = "2007",

doi = "10.1109/CIMCA.2006.46",

language = "English",

isbn = "0769527310",

booktitle = "CIMCA 2006: International Conference on Computational Intelligence for Modelling, Control and Automation, Jointly with IAWTIC 2006: International Conference on Intelligent Agents Web Technologies ...",

note = "CIMCA 2006: International Conference on Computational Intelligence for Modelling, Control and Automation, Jointly with IAWTIC 2006: International Conference on Intelligent Agents Web Technologies and International Commerce ; Conference date: 28-11-2006 Through 01-12-2006",

}

Zhang, P & Kumar, K 2007, Analyzing feature significance from various systems for mass diagnosis. in CIMCA 2006: International Conference on Computational Intelligence for Modelling, Control and Automation, Jointly with IAWTIC 2006: International Conference on Intelligent Agents Web Technologies ...., 4052770, CIMCA 2006: International Conference on Computational Intelligence for Modelling, Control and Automation, Jointly with IAWTIC 2006: International Conference on Intelligent Agents Web Technologies and International Commerce, Sydney, NSW, Australia, 28/11/06. https://doi.org/10.1109/CIMCA.2006.46

Analyzing feature significance from various systems for mass diagnosis. / Zhang, Ping; Kumar, Kuldeep.
CIMCA 2006: International Conference on Computational Intelligence for Modelling, Control and Automation, Jointly with IAWTIC 2006: International Conference on Intelligent Agents Web Technologies .... 2007. 4052770.

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

TY - GEN

T1 - Analyzing feature significance from various systems for mass diagnosis

AU - Zhang, Ping

AU - Kumar, Kuldeep

PY - 2007

Y1 - 2007

N2 - This paper compares a few classification models for mass classification and analyzes the feature significance for mass classification using various models. It involves a few algorithms for feature selection and also analyzes the individual feature significance. The comparison of classification models is based on the same dataseis for mass diagnosis.

AB - This paper compares a few classification models for mass classification and analyzes the feature significance for mass classification using various models. It involves a few algorithms for feature selection and also analyzes the individual feature significance. The comparison of classification models is based on the same dataseis for mass diagnosis.

UR - https://www.scopus.com/pages/publications/38849143996

U2 - 10.1109/CIMCA.2006.46

DO - 10.1109/CIMCA.2006.46

M3 - Conference contribution

SN - 0769527310

SN - 9780769527314

BT - CIMCA 2006: International Conference on Computational Intelligence for Modelling, Control and Automation, Jointly with IAWTIC 2006: International Conference on Intelligent Agents Web Technologies ...

T2 - CIMCA 2006: International Conference on Computational Intelligence for Modelling, Control and Automation, Jointly with IAWTIC 2006: International Conference on Intelligent Agents Web Technologies and International Commerce

Y2 - 28 November 2006 through 1 December 2006

ER -

Analyzing feature significance from various systems for mass diagnosis

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