Abstract: The classic K-Nearest Neighbor (KNN) classification algorithm is widely used in text classification. This paper proposes an efficient algorithm for text classification by improving the ...
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 ...
ABSTRACT: Breast cancer remains one of the most prevalent diseases that affect women worldwide. Making an early and accurate diagnosis is essential for effective treatment. Machine learning (ML) ...
1 Department of Computer Studies, Arab Open University, Riyadh, Saudi Arabia 2 Department of Computer Sciences, ISSAT, University of Gafsa, Gafsa, Tunisia Cybersecurity has become a significant ...
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) ...
Introduction: Atopic dermatitis (AD) is an allergic disease with extreme itching that bothers patients. However, diagnosing AD depends on clinicians’ subjective judgment, which may be missed or ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results