http://researchonline.federation.edu.au/vital/access/manager/Index ${session.getAttribute("locale")} 5 Missing value imputation via clusterwise linear regression http://researchonline.federation.edu.au/vital/access/manager/Repository/vital:14773 In this paper a new method of preprocessing incomplete data is introduced. The method is based on clusterwise linear regression and it combines two well-known approaches for missing value imputation: linear regression and clustering. The idea is to approximate missing values using only those data points that are somewhat similar to the incomplete data point. A similar idea is used also in clustering based imputation methods. Nevertheless, here the linear regression approach is used within each cluster to accurately predict the missing values, and this is done simultaneously to clustering. The proposed method is tested using some synthetic and real-world data sets and compared with other algorithms for missing value imputations. Numerical results demonstrate that the proposed method produces the most accurate imputations in MCAR and MAR data sets with a clear structure and the percentages of missing data no more than 25%

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Discrete gradient methods http://researchonline.federation.edu.au/vital/access/manager/Repository/vital:14699 Wed 07 Apr 2021 14:02:47 AEST ]]> Final words http://researchonline.federation.edu.au/vital/access/manager/Repository/vital:14698 Wed 07 Apr 2021 14:02:47 AEST ]]> Introduction http://researchonline.federation.edu.au/vital/access/manager/Repository/vital:14697 Wed 07 Apr 2021 14:02:47 AEST ]]> Clusterwise support vector linear regression http://researchonline.federation.edu.au/vital/access/manager/Repository/vital:14655 Wed 07 Apr 2021 14:02:44 AEST ]]> Double bundle method for finding clarke stationary points in nonsmooth dc programming http://researchonline.federation.edu.au/vital/access/manager/Repository/vital:13377 Wed 07 Apr 2021 14:01:32 AEST ]]> Clustering in large data sets with the limited memory bundle method http://researchonline.federation.edu.au/vital/access/manager/Repository/vital:13303 Wed 07 Apr 2021 14:01:27 AEST ]]> A proximal bundle method for nonsmooth DC optimization utilizing nonconvex cutting planes http://researchonline.federation.edu.au/vital/access/manager/Repository/vital:11952 Wed 07 Apr 2021 13:57:14 AEST ]]> New diagonal bundle method for clustering problems in large data sets http://researchonline.federation.edu.au/vital/access/manager/Repository/vital:11769 Wed 07 Apr 2021 13:57:02 AEST ]]> Introduction to Nonsmooth Optimization : Theory, practice and software http://researchonline.federation.edu.au/vital/access/manager/Repository/vital:10285 Wed 07 Apr 2021 13:55:38 AEST ]]> Subgradient and bundle methods for nonsmooth optimization http://researchonline.federation.edu.au/vital/access/manager/Repository/vital:6907 Wed 07 Apr 2021 13:46:27 AEST ]]> Limited memory discrete gradient bundle method for nonsmooth derivative-free optimization http://researchonline.federation.edu.au/vital/access/manager/Repository/vital:4800 Wed 07 Apr 2021 13:44:21 AEST ]]> Subgradient Method for Nonconvex Nonsmooth Optimization http://researchonline.federation.edu.au/vital/access/manager/Repository/vital:4733 Wed 07 Apr 2021 13:44:16 AEST ]]> Comparing different nonsmooth minimization methods and software http://researchonline.federation.edu.au/vital/access/manager/Repository/vital:4550 Wed 07 Apr 2021 13:44:01 AEST ]]> Limited Memory Bundle Method for Clusterwise Linear Regression http://researchonline.federation.edu.au/vital/access/manager/Repository/vital:15355 Tue 07 Dec 2021 12:07:47 AEDT ]]> Aggregate subgradient method for nonsmooth DC optimization http://researchonline.federation.edu.au/vital/access/manager/Repository/vital:15031 Mon 21 Mar 2022 14:37:04 AEDT ]]>