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Automatic Control and Computer Sciences

Erschienen in:

01.07.2019

Using Hybrid Discriminative-Generative Models for Binary Classification

verfasst von: N. Abroyan

Erschienen in: Automatic Control and Computer Sciences | Ausgabe 4/2019

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Abstract

Discriminative and generative machine learning algorithms have been successfully used in different classification tasks during the last several decades. They both have some advantages and disadvantages and depending on a problem, one type of algorithm performs better than the other one. In this paper we contribute to the research of combination of both approaches and propose literature based a hybrid discriminative-generative generic model. Also, we propose hybrid model structure finding and building a new algorithm. We present theoretical and practical advantages of the hybrid model over its consisting algorithms, efficiency of the model structure finding algorithm, then perform experiments and compare results.

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Titel: Using Hybrid Discriminative-Generative Models for Binary Classification
verfasst von: N. Abroyan
Publikationsdatum: 01.07.2019
Verlag: Pleiades Publishing
Erschienen in: Automatic Control and Computer Sciences / Ausgabe 4/2019
Print ISSN: 0146-4116
Elektronische ISSN: 1558-108X
DOI: https://doi.org/10.3103/S0146411619040023

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