Hybrid prediction model with missing value imputation for medical data

作者：

Highlights：

• Proposed novel hybrid prediction model with missing value imputation.

• HPM-MI has improved accuracy, sensitivity, specificity, kappa and ROC on 3 datasets.

• The best accuracy is achieved for diabetes, hepatitis, and breast cancer datasets.

• MVI is one of the important step of proposed model.

摘要

•Proposed novel hybrid prediction model with missing value imputation.•HPM-MI has improved accuracy, sensitivity, specificity, kappa and ROC on 3 datasets.•The best accuracy is achieved for diabetes, hepatitis, and breast cancer datasets.•MVI is one of the important step of proposed model.

论文关键词：Missing value imputation,Multilayer Perceptron (MLP),K-means clustering,Data mining

论文评审过程：Available online 4 March 2015.

论文官网地址：https://doi.org/10.1016/j.eswa.2015.02.050