In petroleum geophysics, well logs are fundamental for subsurface characterization; however, missing logs frequently occur due to tool failure, legacy data gaps, or economic constraints, limiting ...

An intrusion detection system (IDS) is a program used to monitor abnormal or irregular behavior in the operation of networks and systems. The system integrates multiple data sources and uses methods ...

Abstract: The research examines the Support Vector Machines (SVM) and K-Nearest Neighbor (KNN) machine learning algorithms with the goal of using machine learning to detect malware and mitigate ...

K-Nearest Neighbors (KNN) is a simple yet effective supervised machine learning algorithm used for both regression and classification tasks. The algorithm works by finding the K nearest data points in ...

Abstract: KNN (k-nearest neighbor) algorithm is an important method which exhibits great performance in many fields. It is a commonly used step in graph convolutional networks (GCN) when graph ...

1 College of Information Science and Technology, Jinan University, Guangzhou, China. 2 University of Birmingham Joint Institute, Jinan University, Guangzhou, China. Text classification is an essential ...

The Internet of Things (IoT) consists of several smart devices equipped with computing, sensing, and network capabilities, which enable them to collect and exchange heterogeneous data wirelessly. The ...

Disease risk prediction is a rising challenge in the medical domain. Researchers have widely used machine learning algorithms to solve this challenge. The k-nearest neighbour (KNN) algorithm is the ...

MuyGPyS is a general-purpose Gaussian process library, similar to GPy, GPyTorch, or GPflow. MuyGPyS differs from the other options in that it constructs approximate GP models using nearest neighbors ...

knncolle is a header-only C++ library that collects a variety of different k-nearest neighbor algorithms under a consistent interface. The aim is to enable downstream libraries to easily switch ...