Multiclass discriminant mappings

Mayer E. Aladjem

doi:10.1016/0165-1684(94)90186-4

Multiclass discriminant mappings

Mayer E. Aladjem

Department of Electrical & Computer Engineering

Research output: Contribution to journal › Article › peer-review

15 Scopus citations

Abstract

Multiclass mappings oriented to the classification of multivariate data are discussed. Parametric and nonparametric mapping criteria are used for single level (one shot) projections. A method for reducing the computation complexity of the optimization procedure is suggested. In the case of a large number of classes, a sequential mapping based on the binary tree scheme is proposed. An algorithm for interactive binary tree design is presented. It combines automated and manual composition of the groups of the classes at the nodes of the tree. An example of the application of the tree mapping is presented.

Original language	English
Pages (from-to)	1-18
Number of pages	18
Journal	Signal Processing
Volume	35
Issue number	1
DOIs	https://doi.org/10.1016/0165-1684(94)90186-4
State	Published - 1 Jan 1994

Keywords

Pattern classification
classifier design
dimensional reduction
exploratory data analysis
mapping of multivariate data

ASJC Scopus subject areas

Control and Systems Engineering
Software
Signal Processing
Computer Vision and Pattern Recognition
Electrical and Electronic Engineering

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10.1016/0165-1684(94)90186-4

Cite this

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title = "Multiclass discriminant mappings",

abstract = "Multiclass mappings oriented to the classification of multivariate data are discussed. Parametric and nonparametric mapping criteria are used for single level (one shot) projections. A method for reducing the computation complexity of the optimization procedure is suggested. In the case of a large number of classes, a sequential mapping based on the binary tree scheme is proposed. An algorithm for interactive binary tree design is presented. It combines automated and manual composition of the groups of the classes at the nodes of the tree. An example of the application of the tree mapping is presented.",

keywords = "Pattern classification, classifier design, dimensional reduction, exploratory data analysis, mapping of multivariate data",

author = "Aladjem, {Mayer E.}",

note = "Funding Information: Correspondence to: Dr. Mayer Aladjem, Department of Electrical and Computer Engineering, Ben-Gurion University of the Negev, P.O. Box 653, Beer-Sheva 84105, Israel. Fax: 972-57-281340; Tel.: 972-57-461841; E-mail: aladjem@bguee.bitnet *This work was supported in part by the Israeli Ministry of Science and Technology under contract number 3548, in part by the Israeli Ministry of Absorption and in part by the Paul Ivanier Center for Robotics and Production Management, Ben Gurion University of the Negev, Israel.",

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doi = "10.1016/0165-1684(94)90186-4",

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N1 - Funding Information: Correspondence to: Dr. Mayer Aladjem, Department of Electrical and Computer Engineering, Ben-Gurion University of the Negev, P.O. Box 653, Beer-Sheva 84105, Israel. Fax: 972-57-281340; Tel.: 972-57-461841; E-mail: aladjem@bguee.bitnet *This work was supported in part by the Israeli Ministry of Science and Technology under contract number 3548, in part by the Israeli Ministry of Absorption and in part by the Paul Ivanier Center for Robotics and Production Management, Ben Gurion University of the Negev, Israel.

PY - 1994/1/1

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N2 - Multiclass mappings oriented to the classification of multivariate data are discussed. Parametric and nonparametric mapping criteria are used for single level (one shot) projections. A method for reducing the computation complexity of the optimization procedure is suggested. In the case of a large number of classes, a sequential mapping based on the binary tree scheme is proposed. An algorithm for interactive binary tree design is presented. It combines automated and manual composition of the groups of the classes at the nodes of the tree. An example of the application of the tree mapping is presented.

AB - Multiclass mappings oriented to the classification of multivariate data are discussed. Parametric and nonparametric mapping criteria are used for single level (one shot) projections. A method for reducing the computation complexity of the optimization procedure is suggested. In the case of a large number of classes, a sequential mapping based on the binary tree scheme is proposed. An algorithm for interactive binary tree design is presented. It combines automated and manual composition of the groups of the classes at the nodes of the tree. An example of the application of the tree mapping is presented.

KW - Pattern classification

KW - classifier design

KW - dimensional reduction

KW - exploratory data analysis

KW - mapping of multivariate data

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U2 - 10.1016/0165-1684(94)90186-4

DO - 10.1016/0165-1684(94)90186-4

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VL - 35

SP - 1

EP - 18

JO - Signal Processing

JF - Signal Processing

IS - 1

ER -

Multiclass discriminant mappings

Abstract

Keywords

ASJC Scopus subject areas

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