A hybrid decision support system based on rough set and extreme learning machine for diagnosis of hepatitis disease
A hybrid model of RS and ELM methods was proposed. Feature selection has been carried out without removing missing values in the data set. RS+ELM model was determined as 100.00% success rate. It is considered that the proposed method will be useful in similar medical practices.
rough set extreme learning machine hepatitis disease dimensionality reduction