Abstract: The K-nearest neighbors (kNNs) algorithm, a cornerstone of supervised learning, relies on similarity measures constrained by real-number-based distance metrics. A critical limitation of ...
Learn how to implement the K-Nearest Neighbors (KNN) algorithm from scratch in Python! This tutorial covers the theory, coding process, and practical examples to help you understand how KNN works ...
The U.S. healthcare system generates massive volumes of data spanning patients, treatments, and billing but real datasets are often inaccessible due to privacy laws like HIPAA. This project was ...
Enhanced SQL injection detection using chi-square feature selection and machine learning classifiers
Computational and Communication Science and Engineering (CoCSE), The Nelson Mandela African Institution of Science and Technology (NM-AIST), Arusha, Tanzania In the face of increasing cyberattacks, ...
Learn the Adagrad optimization algorithm, how it works, and how to implement it from scratch in Python for machine learning models. #Adagrad #Optimization #Python Trump administration looking to sell ...
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 ...
Abstract: The increasing number of breast cancer-related deaths annually underscores the pressing need for improved prediction and diagnostic techniques. Machine learning offers a promising avenue for ...
What if you could turn Excel into a powerhouse for advanced data analysis and automation in just a few clicks? Imagine effortlessly cleaning messy datasets, running complex calculations, or generating ...
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