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Clusterwise support vector linear regression
- Joki, Kaisa, Bagirov, Adil, Karmitsa, Napsu, Mäkelä, Marko, Taheri, Sona
Comparing different nonsmooth minimization methods and software
- Karmitsa, Napsu, Bagirov, Adil, Makela, Marko
Limited memory discrete gradient bundle method for nonsmooth derivative-free optimization
- Karmitsa, Napsu, Bagirov, Adil
New diagonal bundle method for clustering problems in large data sets
- Karmitsa, Napsu, Bagirov, Adil, Taheri, Sona
Clustering in large data sets with the limited memory bundle method
- Karmitsa, Napsu, Bagirov, Adil, Taheri, Sona
Missing value imputation via clusterwise linear regression
- Karmitsa, Napsu, Taheri, Sona, Bagirov, Adil, Makinen, Pauliina
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%
Limited Memory Bundle Method for Clusterwise Linear Regression
- Karmitsa, Napsu, Bagirov, Adil, Taheri, Sona, Joki, Kaisa
Nonsmooth optimization-based hyperparameter-free neural networks for large-scale regression
- Karmitsa, Napsu, Taheri, Sona, Joki, Kaisa, Paasivirta, Pauliina, Defterdarovic, J., Bagirov, Adil, Mäkelä, Marko
Methods and applications of clusterwise linear regression : a survey and comparison
- Long, Qiang, Bagirov, Adil, Taheri, Sona, Sultanova, Nargiz, Wu, Xue
Subgradient and bundle methods for nonsmooth optimization
- Makela, Marko, Karmitsa, Napsu, Bagirov, Adil
Adaption to water shortage through the implementation of a unique pipeline system in Victoria, Australia
- Mala-Jetmarova, Helena, Barton, Andrew, Bagirov, Adil, McRae-Williams, Pamela, Caris, Rob, Jackson, Peter
Optimal operation of a multi-quality water distribution system with changing turbidity and salinity levels in source reservoirs
- Mala-Jetmarova, Helena, Barton, Andrew, Bagirov, Adil
- Mala-Jetmarova, Helena, Bagirov, Adil, Barton, Andrew
- Mala-Jetmarova, Helena, Bagirov, Adil, Barton, Andrew
- Mala-Jetmarova, Helena, Barton, Andrew, Bagirov, Adil
- Mala-Jetmarova, Helena, Barton, Andrew, Bagirov, Adil
- Mala-Jetmarova, Helena, Barton, Andrew, Bagirov, Adil
A history of water distribution systems and their optimisation
- Mala-Jetmarova, Helena, Barton, Andrew, Bagirov, Adil
Integrated production system optimization using global optimization techniques
- Mason, T. L., Emelle, C., Van Berkel, J., Bagirov, Adil, Kampas, F., Pinter, J. D.
A convolutional recursive modified Self Organizing Map for handwritten digits recognition
- Mohebi, Ehsan, Bagirov, Adil
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