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 ...
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 ...
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 ...
Abstract: This work aims to compare two different Feature Extraction Algorithms (FEAs) viz. Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA), using a K-Nearest Neighbor (KNN) ...
ABSTRACT: To ensure the efficient operation and timely maintenance of wind turbines, thereby enhancing energy security, it is critical to monitor the operational status of wind turbines and promptly ...
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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