Classical and Incremental Classification in Data Mining Process

Knowledge Discovery in Databases (KDD) is an iterative and multi step process that aims at extracting previously unknown and hidden patterns from a huge volume of databases. Data mining is a stage of the entire KDD process that involves applying a particular data mining algorithm to extract an interesting knowledge. One of the important problems that are used by data mining community is so-called classification problem. In this paper the authors study the classification task and provide a comprehensive study of classification techniques with more emphasis on classical and incremental decision tree based classification.