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Parametric Optimization of the Selected Classifiers in Binary Classification

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

3 Citations (Scopus)

Abstract

The conception of classification is one of the major aspects in data processing. Conducted research present comparison of chosen classifiers’ results of classification for a few data sets. All data were chosen from these available on UCI Machine Learning Repository web site. During realization of research, the optimization process of the results of classification was made on the modifiable parameters for particular classifiers. In this work, gathered result of classification was presented as well as conclusion and possibility of future work.

Original languageEnglish
Title of host publicationStudies in Computational Intelligence
PublisherSpringer Verlag
Pages59-69
Number of pages11
DOIs
Publication statusPublished - 1 Mar 2017

Publication series

NameStudies in Computational Intelligence
Volume710
ISSN (Print)1860-949X

Keywords

  • Accuracy
  • Classification
  • Classifier
  • IBk
  • Logistic Base
  • Naive Bayes
  • Optimization
  • Parameter
  • SGD
  • SMO
  • UCI
  • Voted Perceptron
  • WEKA
  • Zero R

ASJC Scopus subject areas

  • Artificial Intelligence

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