Abstract:
Data mining is the process of discovering useful
information underlying the data. Powerful
techniques are needed to extract patterns from large
data because traditional statistical tools are
efficient enough any more. Classification and
prediction are two forms of data analysis that can
be used predict future data trends. In this paper, we
proposed a diagnosis system for Hypothyroid
disease by using decision tree induction algorithm.
Decision tree induction algorithms have been used
for classification in a wide range of application
domains. Decision trees are potentially powerful
predictors and explicitly represent the structure of a
dataset. In this system, C4.5 classification algorithm
is analyzed to build the model from a given set of
training data and then produced classification rules.
It examines the patient is positive or negative in
hypothyroid. The performance evaluation of our
system is also discussed in this paper.
