Abstract:
Data classification is the process of building a
model from available data called the training
dataset and classifying object according to their
attributes. A derived model may be represented in
various forms, such as decision tree, mathematical
formula and neural networks. Decision tree
algorithm has been used for classification in a wide
range of application domains. In this paper, we
propose a new system that tests the level of
depression by using decision tree induction
classification algorithm. Depending upon the data
tuples of patient’s symptom dataset, the system can
classify the level of depression within a minimum of
time. This system will be implemented by using
C#(2005) and SQLSever 2000.
