A study of the data pre-processing module of the dendritic cell evolutionary algorithm

Data reduction as a critical step in the process of data pre-processing presents a central point of interest across a wide variety of fields. Data pre-processing has a significant impact on the performance of any machine learning algorithm. In this context, we focus our research paper on investigating the data pre-processing phase of a recent evolutionary algorithm named the Dendritic Cell Algorithm (DCA). We aim at reviewing the data pre-processing phase of the DCA while making a comparative study of the used data reduction techniques within the DCA. This is needed to clarify the differences, the advantages and the characteristics of the previously proposed techniques with the DCA. The output of the comparison will facilitate the task of the developer to select the most useful technique to be adopted and integrated in the DCA data pre-processing module.