Smart prototype selection for machine learning based on ignorance zones analysis

Smart prototype selection for machine learning based on ignorance zones analysis

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The size of databases has been considerably growing over recent decades and Machine Learning algorithms are not ready to process such large volume of information. Being one of the most useful algorithms in Data Mining the Nearest neighbor classifier suffers from high storage requirements and slow re...

Täydet tiedot

Bibliografiset tiedot
Päätekijä: Nikulin, Anton
Muut tekijät: Informaatioteknologian tiedekunta, Faculty of Information Technology, Information Technology, Informaatioteknologia, University of Jyväskylä, Jyväskylän yliopisto
Aineistotyyppi: Pro gradu
Kieli:eng
Julkaistu: 2018
Aiheet:
Prototype selection
Nearest neighbor
Ignorance zones
Data reduction
Classification
Tietotekniikka
Mathematical Information Technology
602
prototyypit
koneoppiminen
Linkit: https://jyx.jyu.fi/handle/123456789/57461

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