IEEE

Sparse Coefficient-Based ${k}$ -Nearest Neighbor Classification

Abstract: K-nearest neighbor rule (KNN) and sparse representation (SR) are widely used algorithms in pattern classification. In this paper, we propose two new nearest neighbor classification methods, ...
GitHub

CUDA-Based Parallel Processing for Diabetes Classification Using K-Nearest Neighbor

The CPU and GPU confusion matrices are nearly identical. The prediction agreement between both implementations reached 99.82%, showing that the CUDA implementation preserved the classification ...
IEEE

A k-nearest neighbor based algorithm for multi-label classification

Abstract: In multi-label learning, each instance in the training set is associated with a set of labels, and the task is to output a label set whose size is unknown a priori for each unseen instance.
RMD Open

Development and assessment of an assisted diagnosis model using machine learning for identifying adult-onset Still’s disease in fever of unknown origin: a retrospective …

Background Adult-onset Still’s disease (AOSD) is a systemic autoinflammatory disorder lacking a gold-standard diagnostic ...
C&EN

Effect of Molecular Descriptor Feature Selection in Support Vector Machine Classification of Pharmacokinetic and Toxicological Properties of Chemical Agents

Department of Computational Science, National University of Singapore, Blk SOC1, Level 7, 3 Science Drive 2, Singapore 117543, Singapore-MIT Alliance, E-04-10, 4 Engineering Drive 3, Singapore, 117576 ...
GitHub

anushka123jet-cloud/KNN-Classifier-Implementation

🚀 K-Nearest Neighbors (KNN) Classifier Implementation This repository demonstrates the implementation of the K-Nearest Neighbors (KNN) classification algorithm using Python and Scikit-learn. It walks ...
C&EN

Real-Time and Rapid Food Quality Monitoring Using Smart Sensory Films with Image Analysis and Machine Learning

Department of Agricultural and Biological Engineering, University of Florida, P.O. Box 110570, Gainesville, Florida 32611, United States ...