Abstract:
Heart Disease was the major cause of causalities
in most of the countries. According to the medical
records, heart disease kills one person in very sort
time. Classification and prediction are the forms of
data analysis that can be used to extract models for
important classes or to predict future data trends. In
this paper, decision tree induction algorithm is used
to classify the risk level for heart disease. Decision
tree is a flow-chart-like tree structure, where each
internal node denotes a test on an attributes, each
branch represents an outcome of the test, and the
leaf nodes represent classes or class distributions.
This system generates the understandable rules for
user and estimates the accuracy for classifier.
Depending on the attribute values of the data set,
this system can classify the risk level of heart
disease whether it is in serious or normal conditions
for patients. Thus, the user can test his or her
medical check concerned with their heart.
Moreover, the system can provide the classifier
accuracy by using Holdout Method.
