An improved imputation method based on fuzzy c-means and particle swarm optimization for missing data

Data mining techniques are used in various industries, including database marketing, web analysis, information retrieval and bioinformatics to gain a better knowledge extraction. However, if data mining techniques are applied on real datasets, a problem that often comes up is that missing values occ...

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Main Author: Samat, Nurul Ashikin
Format: Thesis
Language:en
en
en
Published: 2017
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Online Access:http://eprints.uthm.edu.my/7817/2/24p%20NURUL%20ASHIKIN%20SAMAT.pdf
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http://eprints.uthm.edu.my/7817/
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author Samat, Nurul Ashikin
author_facet Samat, Nurul Ashikin
author_sort Samat, Nurul Ashikin
building UTHM Library
collection Institutional Repository
content_provider Universiti Tun Hussein Onn Malaysia
content_source UTHM Institutional Repository
continent Asia
country Malaysia
description Data mining techniques are used in various industries, including database marketing, web analysis, information retrieval and bioinformatics to gain a better knowledge extraction. However, if data mining techniques are applied on real datasets, a problem that often comes up is that missing values occur in the datasets. Since the missing values may confuse the data mining process and causing the knowledge extracted unreliable, there is a need to handle the missing values. Therefore, researchers ar.e coming out with imputation methods in the preproce_ssing
format Thesis
id my.uthm.eprints-7817
institution Universiti Tun Hussein Onn Malaysia
language en
en
en
publishDate 2017
record_format eprints
spelling my.uthm.eprints-78172022-10-12T02:21:28Z http://eprints.uthm.edu.my/7817/ An improved imputation method based on fuzzy c-means and particle swarm optimization for missing data Samat, Nurul Ashikin QA Mathematics QA71-90 Instruments and machines Data mining techniques are used in various industries, including database marketing, web analysis, information retrieval and bioinformatics to gain a better knowledge extraction. However, if data mining techniques are applied on real datasets, a problem that often comes up is that missing values occur in the datasets. Since the missing values may confuse the data mining process and causing the knowledge extracted unreliable, there is a need to handle the missing values. Therefore, researchers ar.e coming out with imputation methods in the preproce_ssing 2017-08 Thesis NonPeerReviewed text en http://eprints.uthm.edu.my/7817/2/24p%20NURUL%20ASHIKIN%20SAMAT.pdf text en http://eprints.uthm.edu.my/7817/1/NURUL%20ASHIKIN%20SAMAT%20COPYRIGHT%20DECLARATION.pdf text en http://eprints.uthm.edu.my/7817/3/NURUL%20ASHIKIN%20SAMAT%20WATERMARK.pdf Samat, Nurul Ashikin (2017) An improved imputation method based on fuzzy c-means and particle swarm optimization for missing data. Masters thesis, Universiti Tun Hussein Onn Malaysia.
spellingShingle QA Mathematics
QA71-90 Instruments and machines
Samat, Nurul Ashikin
An improved imputation method based on fuzzy c-means and particle swarm optimization for missing data
title An improved imputation method based on fuzzy c-means and particle swarm optimization for missing data
title_full An improved imputation method based on fuzzy c-means and particle swarm optimization for missing data
title_fullStr An improved imputation method based on fuzzy c-means and particle swarm optimization for missing data
title_full_unstemmed An improved imputation method based on fuzzy c-means and particle swarm optimization for missing data
title_short An improved imputation method based on fuzzy c-means and particle swarm optimization for missing data
title_sort improved imputation method based on fuzzy c-means and particle swarm optimization for missing data
topic QA Mathematics
QA71-90 Instruments and machines
url http://eprints.uthm.edu.my/7817/2/24p%20NURUL%20ASHIKIN%20SAMAT.pdf
http://eprints.uthm.edu.my/7817/1/NURUL%20ASHIKIN%20SAMAT%20COPYRIGHT%20DECLARATION.pdf
http://eprints.uthm.edu.my/7817/3/NURUL%20ASHIKIN%20SAMAT%20WATERMARK.pdf
http://eprints.uthm.edu.my/7817/
url_provider http://eprints.uthm.edu.my/