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A machine learning-based methodology to uniquely identify network devices using DNS query patterns, combining unsupervised clustering (K-Means) with supervised classification (Random Forest).
Abstract: The purpose of this research is to determine whether or not the Random Forest (RF) algorithm is superior to the Linear Discriminant Analysis (LDA) method in terms of accuracy, recall, ...
Abstract: The signature base technique cannot recognize new types of Ransomware without first analyzing it. For that, we need a method to detect Ransomware using machine learning. This study aims to ...
Dr. James McCaffrey presents a complete end-to-end example of random forest regression to predict a single numeric value, implemented using C#. A random forest is a collection of basic decision tree ...