Classification of large datasets using Random Forest Algorithm in various applications: Survey

Journal Article

Zakariah, Mohammed . 2014

• رابط المنشور على الويب: http://www.ijeit.com/Vol%204/Issue%203/IJEIT1412201409_28.pdf
• المجلة \ الصحيفة: International Journal of Engineering and Innovative Technology (IJEIT)
• رقم العدد: 3
• رقم الإصدار السنوي: 4
• الصفحات: 189-198

مستخلص المنشور

Random Forest is an ensemble of classification algorithm widely used in much application especially with larger datasets because of its outstanding features like Variable Importance measure, OOB error detection, Proximity among the feature and handling of imbalanceddatasets. This paper discusses many applications which use Random Forest to classify the dataset like Network intrusion detection, Email spam detection, gene classification, Credit card fraud detection, and Text classification. In this paper each application is briefly introduced and then the dataset used for implementation is discussed and finally the real implementation of Random Forest algorithm with steps wise procedure and also the results are discussed. Actual Random Forest Algorithm and its features are also discussed to highlight the main features of Random Forest Algorithm more clearly.