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Published on: October 11, 2018
A Comparison of Decision Tree Algorithms in the Assessment of Biomedical Data
Fahima Hajjej1, Manal Abdullah Alohali1, Malek Badr2,3
1Department of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia.
Abstract:
By comparing the performance of various tree algorithms, we can determine which one is most useful for analyzing biomedical data. In artificial intelligence, decision trees are a classification model known for their visual aid in making decisions. WEKA software will evaluate biological data from real patients to see how well the decision tree classification algorithm performs. Another goal of this comparison is to assess whether or not decision trees can serve as an effective tool for medical diagnosis in general. In doing so, we will be able to see which algorithms are the most efficient and appropriate to use when delving into this data and arrive at an informed decision.
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