A Generalized Decision Tree Using Relevance Analysis To Evaluate Condition Attributes

Data mining is an advanced process, in which we can pick up many trustful, operative, useful and readable patterns from very lager amounts of data, also be called as KDD(Knowledge Discovery in Database). Classification is a key data mining technique whereby database tuples, acting as training samples, are analyzed in order to produce a model of the given data. Each tuple is assumed to belong to a predefined class, as determined by one of the attributes, called the classifying attribute. Once derived, the classification model can be used to categorize future data samples, as well as provide a better understanding of the database contents. Classification has numerous applications including credit approval, product marketing, and medical diagnosis.Decision tree classifiers have found the widest application in large-scale data mining environments. There are several reasons for this. First, decision trees offer a very intuitive representation that is easy to...