Yiǧilmiş genelleme algoritmasinda öznitelik füzyonunun kuramsal analizi

Translated title of the contribution: A theoretical analysis of feature fusion in stacked generalization

Mete Ozay, Fatoş T. Yarman Vural

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

In the present work, a theoretical framework in order to define the general performance of stacked generalization learning algorithm is developed. Analytical relationships between the performance of the Stacked Generalization classifier relative to the individual classifiers are constructed by the proposed theorems and the practical techniques are developed in order to optimize the performance of stacked generalization algorithm based on these relationships.

Translated title of the contributionA theoretical analysis of feature fusion in stacked generalization
Original languageTurkish
Title of host publication2009 IEEE 17th Signal Processing and Communications Applications Conference, SIU 2009
Pages548-551
Number of pages4
DOIs
Publication statusPublished - 2009 Oct 29
Event2009 IEEE 17th Signal Processing and Communications Applications Conference, SIU 2009 - Antalya, Turkey
Duration: 2009 Apr 92009 Apr 11

Publication series

Name2009 IEEE 17th Signal Processing and Communications Applications Conference, SIU 2009

Conference

Conference
CountryTurkey
CityAntalya
Period09/4/909/4/11

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Signal Processing
  • Communication

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