An Overview of Existing Machine Learning Methods for Gender Classification of Names

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dc.citation.epage92
dc.citation.spage91
dc.contributor.affiliationNational Technical University "Kharkiv Polytechnic Institute"
dc.contributor.authorShleiko, Anna
dc.contributor.authorBorysova, Natalia
dc.contributor.authorKochuieva, Zoia
dc.contributor.authorMelnyk, Karina
dc.coverage.placenameЛьвів ; Харків
dc.coverage.placenameLviv ; Kharkiv
dc.coverage.temporal22-23 April 2021, Kharkiv
dc.date.accessioned2022-05-23T10:50:11Z
dc.date.available2022-05-23T10:50:11Z
dc.date.created2021-05-04
dc.date.issued2021-05-04
dc.description.abstractThe paper presents an overview of the existing machine learning methods for solving the problem of gender classification of the authors of the written texts by names: substantiates the relevance of the research topic, analyzes the existing methods of solving the task and selects the direction of further research.
dc.format.extent91-92
dc.format.pages2
dc.identifier.citationAn Overview of Existing Machine Learning Methods for Gender Classification of Names / Anna Shleiko, Natalia Borysova, Zoia Kochuieva, Karina Melnyk // Computational linguistics and intelligent systems, 22-23 April 2021, Kharkiv. — Lviv ; Kharkiv, 2021. — Vol Vol. II : Proceedings of the 5th International conference, COLINS 2021, Workshop, Kharkiv, Ukraine, April 22-23. — P. 91–92.
dc.identifier.citationenAn Overview of Existing Machine Learning Methods for Gender Classification of Names / Anna Shleiko, Natalia Borysova, Zoia Kochuieva, Karina Melnyk // Computational linguistics and intelligent systems, 22-23 April 2021, Kharkiv. — Lviv ; Kharkiv, 2021. — Vol Vol. II : Proceedings of the 5th International conference, COLINS 2021, Workshop, Kharkiv, Ukraine, April 22-23. — P. 91–92.
dc.identifier.issn2523-4013
dc.identifier.urihttps://ena.lpnu.ua/handle/ntb/56805
dc.language.isoen
dc.relation.ispartofComputational linguistics and intelligent systems, 2021
dc.relation.references[1] A. Sidath, Machine Learning Classifiers, 2018. URL: https://towardsdatascience.com/ machinelearning-classifiers-a5cc4e1b0623
dc.relation.references[2] E. Alpaydin, Introduction to Machine Learning, third, 3rd. ed., MIT Press, Cambridge, MA, 2015.
dc.relation.references[3] R. Garg, 7 Types of Classification Algorithms. URL: https://analyticsindiamag.com/7-typesclassification-algorithms
dc.relation.referencesen[1] A. Sidath, Machine Learning Classifiers, 2018. URL: https://towardsdatascience.com/ machinelearning-classifiers-a5cc4e1b0623
dc.relation.referencesen[2] E. Alpaydin, Introduction to Machine Learning, third, 3rd. ed., MIT Press, Cambridge, MA, 2015.
dc.relation.referencesen[3] R. Garg, 7 Types of Classification Algorithms. URL: https://analyticsindiamag.com/7-typesclassification-algorithms
dc.relation.urihttps://towardsdatascience.com/
dc.relation.urihttps://analyticsindiamag.com/7-typesclassification-algorithms
dc.rights.holdercopyrighted by its editors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
dc.rights.holder© 2021 Copyright for the individual papers by the papers’ authors. Copying permitted only for private and academic purposes. This volume is published and
dc.subjectGender classification
dc.subjectsupervised machine learning
dc.subjectmethods of classification
dc.titleAn Overview of Existing Machine Learning Methods for Gender Classification of Names
dc.typeArticle

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