GBKII: An imputation method for missing values

DSpace/Manakin Repository

Search OPUS


Advanced Search

Browse

My Account

Show simple item record

dc.contributor.author Zhang, C
dc.contributor.author Zhu, X
dc.contributor.author Zhang, J
dc.contributor.author Qin, Y
dc.contributor.author Zhang, S
dc.date.accessioned 2009-11-09T02:45:35Z
dc.date.issued 2007
dc.identifier.citation Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2007, 4426 LNAI pp. 1080 - 1087
dc.identifier.isbn 9783540717003
dc.identifier.issn 0302-9743
dc.identifier.other E1 en_US
dc.identifier.uri http://hdl.handle.net/10453/1867
dc.description.abstract Missing data imputation is an actual and challenging issue in machine learning and data mining. This is because missing values in a dataset can generate bias that affects the quality of the learned patterns or the classification performances. To deal with this issue, this paper proposes a Grey-Based K-NN Iteration Imputation method, called GBKII, for imputing missing values. GBKII is an instance-based imputation method, which is referred to a non-parametric regression method in statistics. It is also efficient for handling with categorical attributes. We experimentally evaluate our approach and demonstrate that GBKII is much more efficient than the k-NN and mean-substitution methods. © Springer-Verlag Berlin Heidelberg 2007.
dc.title GBKII: An imputation method for missing values
dc.type Conference Proceeding
dc.parent Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.journal.volume 4426 LNAI
dc.journal.number en_US
dc.publocation Berlin, Germany en_US
dc.identifier.startpage 1080 en_US
dc.identifier.endpage 1087 en_US
dc.cauo.name QCIS Investment Core en_US
dc.conference Verified OK en_US
dc.conference.location Nanjing, China en_US
dc.for 0801 Artificial Intelligence and Image Processing
dc.personcode 020030
dc.personcode 011221
dc.percentage 100 en_US
dc.classification.name Artificial Intelligence and Image Processing en_US
dc.classification.type FOR-08 en_US
dc.custom Pacific-Asia Conference on Knowledge Discovery and Data Mining en_US
dc.date.activity 20070522 en_US
dc.location.activity Nanjing, China en_US
pubs.embargo.period Not known
pubs.organisational-group /University of Technology Sydney
pubs.organisational-group /University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group /University of Technology Sydney/Strength - Quantum Computation and Intelligent Systems


Files in this item

This item appears in the following Collection(s)

Show simple item record