ABSTRACT: This paper evaluates the performance of multiple machine learning models in predicting NBA game outcomes. Both regression and classification approaches were explored, with models including ...

To understand and implement the K-Nearest Neighbors (KNN) algorithm for solving classification problems using the Iris dataset. This project demonstrates data preprocessing, model training, evaluation ...

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 ...

Physical frailty is a pressing public health issue that significantly increases the risk of disability, hospitalization, and mortality. Early and accurate detection of frailty is essential for timely ...

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) ...

Abstract: The K-Nearest Neighbor algorithm is a supervised machine learning algorithm that is used for classification problems. The execution time of this algorithm could be extremely high, especially ...