Abstract: This research article identifies the fault occurrence in the blowfish cryptography algorithm using a modified Decision Tree classifier. Though there are several cryptography algorithms, the ...
Abstract: A fall-detection system was implemented utilizing a 2.45 GHz continuous wave radar along with power-efficient and fully-analog integrated classifier architectures. The Power Burst Curve and ...
This review presents a unified, efficient model of random decision forests which can be applied to a number of machine learning, computer vision, and medical image analysis tasks. Our model extends ...
We developed a novel algorithm to train robust decision tree based models (notably, Gradient Boosted Decision Tree). This repo contains our implementation under the XGBoost framework. We plan to merge ...
Service-based organizations may handle thousands of customer emails daily, placing a significant burden on IT help desks, customer service organizations, and other departments involved in reading, ...
In the context of the rapid development of intelligent manufacturing, the stable operation of mechanical equipment is crucial for maintaining industrial production continuity and achieving economic ...
Detection and analysis of spontaneous synaptic events is an extremely common task in many neuroscience research labs. Various algorithms and tools have been developed over the years to improve the ...
STreeD is a framework for optimal binary decision trees with separable optimization tasks. A separable optimization task is a task that can be optimized separately for the left and right subtree. The ...
Exposure to domestic abuse can lead to long-term negative impacts on the victim's physical and psychological wellbeing. The 1998 Crime and Disorder Act requires agencies to collaborate on crime ...
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