A Survey on Pre-processing and Post-processing Techniques in Data Mining
Divya Tomar, Sonali Agarwal · International Journal of Database Theory and Application · 2014
Knowledge Discovery in Databases (KDD) covers various processes of exploring useful information from voluminous data.These data may contain several inconsistencies, missing records or irrelevant features, which make the knowledge extraction, a difficult process.So, it is essential to apply pre-processing techniques to these data in order to enhance its quality.Detailed description of data cleaning, imbalanced data handling and dimensionality reduction pre-processing techniques are depicted in this paper.Another important aspect of Knowledge Discovery is to filter, integrate, visualize and evaluate the extracted knowledge.In this paper, several visualization techniques such as scatter plots, parallel co-ordinates and pixel oriented technique are explained.The paper also includes detail descriptions of three visualization tools which are DBMiner, Spotfire and WinViz along with their comparative evaluation on the basis of certain criteria.It also highlights the research opportunities and challenges of Knowledge Discovery process.