Developing Decision Tree Using ID3 for Depression Testing

Data classification is the process of building amodel from available data called the trainingdataset and classifying object according to theirattributes. A derived model may be represented invarious forms, such as decision tree, mathematicalformula and neural networks. Decision treealgorithm has been used for classification in a widerange of application domains. In this paper, wepropose a new system that tests the level ofdepression by using decision tree inductionclassification algorithm. Depending upon the datatuples of patient’s symptom dataset, the system canclassify the level of depression within a minimum oftime. This system will be implemented by usingC#(2005) and SQLSever 2000