Data Mining with Weka Heart Disease Dataset
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چکیده
The dataset used in this exercise is the heart disease dataset available in heart-c.arff obtained from the UCI repository. This dataset describes risk factors for heart disease. The attribute num represents the (binary) class attribute: class <50 means no disease; class >50_1 indicates increased level of heart disease. The main aim of this exercise is to predict heart disease from the other attributes in the dataset. Obviously, this is a classification problem. The software to be used is Weka 3.6 . However, feel free to try any ideas you may have to tackle the problem with any other software. The description of this exercise is stepwise. Therefore, I hope you can get a better understanding of the various aspects and questions involved in the KDD process.
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