Title
Imputation methods outperform missing-indicator for data missing completely at random
Author
Pereira Barata, A.
Takes, F.W.
van den Herik, H.J.
Veenman, C.J.
Contributor
He, X. (editor)
Papapetrou, Q. (editor)
Cheng, P. (editor)
Publication year
2019
Subject
Classification
Data preprocessing
Imputation
Missing data
Missing-indicator method
Data Analytics
Data handling
Data mining
Nearest neighbor search
Numerical methods
Open Data
Radial basis function networks
Support vector machines
Classifier performance
Complete classification
Data preprocessing
Imputation
Indicator methods
Missing data
Support vector machine classifiers
Tree-based ensemble classifiers
Classification (of information)
To reference this document use:
http://resolver.tudelft.nl/uuid:cd8784aa-f45f-4568-8060-5fb7cc3be55b
TNO identifier
955096
Publisher
IEEE Computer Society
ISBN
9781728146
ISSN
2375-9232
Source
IEEE International Conference on Data Mining Workshops, ICDMW, 19th IEEE International Conference on Data Mining Workshops, ICDMW 2019, 8 November 2019 through 11 November 2019, 407-414
Document type
conference paper