Missing Data Imputation for Continuous Variables Based on Multivariate Adaptive Regression Splines-Reference-Cited by-同舟云学术

Missing Data Imputation for Continuous Variables Based on Multivariate Adaptive Regression Splines

Published:2020 Issue: Volume: Page:73-85
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
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Author:

Sánchez Lasheras Fernando^ORCID,García Nieto Paulino José^ORCID,García-Gonzalo Esperanza^ORCID,Argüeso Gómez Francisco^ORCID,Rodríguez Iglesias Francisco Javier^ORCID,Suárez Sánchez Ana^ORCID,Santos Rodríguez Jesús Daniel^ORCID,Sánchez María Luisa^ORCID,González-Nuevo Joaquín^ORCID,Bonavera Laura^ORCID,Toffolatti Luigi^ORCID,Fernández Menéndez Susana del Carmen^ORCID,de Cos Juez Francisco Javier^ORCID

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-61705-9_7

Reference18 articles.

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2. van Buuren, S., Groothuis-Oudshoorn, K.: mice: multivariate imputation by chained equations in R. J. Stat. Softw. 45(3), 1–67 (2011)

3. Ordóñez Galán, C., Sánchez Lasheras, F., de Cos Juez, F.J., Bernardo Sánchez, A.: Missing data imputation of questionnaires by means of genetic algorithms with different fitness functions. J. Comput. Appl. Math. 311, 704–717 (2017)

4. Honaker, J., King, G., Blackwell, M.: Amelia II: a program for missing data. J. Stat. Softw. 45(7), 1–47 (2011)

5. Wang, X., Li, A., Jiang, Z., Feng, H.: Missing value estimation for DNA microarray gene expression data by support vector regression imputation and orthogonal coding scheme. BMC Bioinform. 7(1), 1 (2006)

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