Abstract: The purpose of this research is to create and evaluate a clever K Nearest Neighbor-based systematic prediction system against the Decision Tree Classifier method for early flood detection in ...
ABSTRACT: The objective of this work is to determine the true owner of a land—public or private—in the region of Kumasi (Ghana). For this purpose, we applied different machine learning methods to the ...
ABSTRACT: Cybersecurity has emerged as a global concern, amplified by the rapid expansion of IoT devices and the growing digitization of systems. In this context, traditional security solutions such ...
Background: Patients undergoing maintenance hemodialysis face a high mortality rate, yet effective tools for predicting mortality risk in this population are lacking. This study aims to develop an ...
This repository contains the implementation of a hardware-accelerated K-Nearest Neighbors (KNN) algorithm using Verilog on an FPGA. The project includes performance and timing analysis using Quartus, ...
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Adadelta Algorithm from Scratch in Python
Learn how the Adadelta optimization algorithm really works by coding it from the ground up in Python. Perfect for ML enthusiasts who want to go beyond the black box! Florida State Bracing for Hefty ...
Abstract: The K-Nearest Neighbors (kNN) algorithm, a cornerstone of supervised learning, relies on similarity measures constrained by real-number-based distance metrics. A critical limitation of ...
This project demonstrates how to implement the K-Nearest Neighbors (KNN) algorithm for classification on a customer dataset. The program iterates through different values of k (number of neighbors) ...
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