Knowledge discovery and a comparison of data mining tools on iris dataset

Nowadays, there are large amount of data being kept on many databases that are related to many areas. One of the basic aims of KDD (knowledge discovery in databases) is to extract the knowledge from these large amount of data associated with each other, meaningful and not found before. During the process of KDD, the resulting such information or rather knowledge by interpreting and combining with other knowledge if necessary, is knowledge discovery in databases. DM (data mining) on the other hand is one of the crucial steps of KDD. In this thesis study, main objective is to show the relationship between knowledge discovery in databases (KDD) and data mining (DM). After the needed review and research, a data mining application on an available data which is called ?IRIS dataset? is performed using some data mining tools. Results of these performed applications are compared with each other. The key objective of the study is to prepare an initial step for further applications with real data.