A new imputation method based on genetic programming and weighted KNN for symbolic regression with incomplete data

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@Article{DBLP:journals/soco/Al-Helali00021,

• author = "Baligh Al-Helali and Qi Chen and Bing Xue and Mengjie Zhang",
• title = "A new imputation method based on genetic programming and weighted {KNN} for symbolic regression with incomplete data",
• journal = "Soft Computing",
• volume = "25",
• number = "8",
• pages = "5993--6012",
• year = "2021",
• month = apr,
• keywords = "genetic algorithms, genetic programming, Symbolic regression, Incomplete data, KNN, Imputation",
• ISSN = "1432-7643",
• URL = "https://doi.org/10.1007/s00500-021-05590-y",
• DOI = "doi:10.1007/s00500-021-05590-y",
• timestamp = "Wed, 07 Apr 2021 01:00:00 +0200",
• biburl = "https://dblp.org/rec/journals/soco/Al-Helali00021.bib",
• bibsource = "dblp computer science bibliography, https://dblp.org",
• abstract = "Incompleteness is one of the problematic data quality challenges in real-world machine learning tasks. A large number of studies have been conducted for addressing this challenge. However, most of the existing studies focus on the classification task and only a limited number of studies for symbolic regression with missing values exist. a new imputation method for symbolic regression with incomplete data is proposed. The method aims to improve both the effectiveness and efficiency of imputing missing values for symbolic regression. This method is based on genetic programming (GP) and weighted K-nearest neighbors (KNN). It constructs GP-based models using other available features to predict the missing values of incomplete features. The instances used for constructing such models are selected using weighted KNN. The experimental results on real-world data sets show that the proposed method outperforms a number of state-of-the-art methods with respect to the imputation accuracy, the symbolic regression performance, and the imputation time.",

}

Genetic Programming entries for Baligh Al-Helali Qi Chen Bing Xue Mengjie Zhang

Citations