Comparative Study of Four Supervised Machine Learning Techniques for Classification
Amr E. Mohamed

Abstract
A comparative study of four well-known supervised machine learning techniques namely; Decision Tree, KNearest- Neighbor, Artificial-Neural-Network and Support Vector Machine has been conducted. This paper concentrated on the key ideas of each technique and its advantages and disadvantages. Practical application has been conducted at the end of the study to compare their performance. Some measures have been used for evaluating their performance, such as sensitivity and specificity. This study had shown that there is no one measure can provide everything about the classifier performance and there is no such classifier that can satisfy all the criterion.

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