Impact of imputation of missing values on classification error for discrete data

DOI10.1016/j.patcog.2008.05.019zbMath1173.68479OpenAlexW2159798994WikidataQ56993296 ScholiaQ56993296MaRDI QIDQ948003

Alireza Farhangfar, Jennifer G. Dy, Lukasz A. Kurgan

Publication date: 8 October 2008

Published in: Pattern Recognition (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.patcog.2008.05.019

zbMATH Keywords

classificationmissing valuesmultiple imputationssingle imputationimputation of missing values

Mathematics Subject Classification ID

Database theory (68P15) Learning and adaptive systems in artificial intelligence (68T05) Pattern recognition, speech recognition (68T10)

Related Items (14)

Matrix completion discriminant analysis ⋮ Impact of Imputation Strategies on Fairness in Machine Learning ⋮ Regression with missing data, a comparison study of techniques based on random forests ⋮ Evidence integration credal classification algorithm versus missing data distributions ⋮ Recursive partitioning on incomplete data using surrogate decisions and multiple imputation ⋮ Distance estimation in numerical data sets with missing values ⋮ Neuro-rough-fuzzy approach for regression modelling from missing data ⋮ Rough subspace neuro-fuzzy system ⋮ The theoretic framework of local weighted approximation for microarray missing value estimation ⋮ Learn\(^{++}\).MF: A random subspace approach for the missing feature problem ⋮ A delay-resilient and quality-aware mechanism over incomplete contextual data streams ⋮ Robust K-Median and K-means clustering algorithms for incomplete data ⋮ Techniques for dealing with incomplete data: a tutorial and survey ⋮ Racing trees to query partial data

Uses Software

• UCI-ml
• LERS
• MICE
• C4.5

Cites Work

• Imputation techniques in regression analysis: Looking closely at their implementation
• Multiple Imputation After 18+ Years
• Imputation using markov chains
• Formalizing Subjective Notions About the Effect of Nonrespondents in Sample Surveys
• A test of missing completely at random for generalised estimating equations with missing data
• Variational Bayesian Learning of ICA with Missing Data
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