PL-kNN: A Python-based implementation of a parameterlessk-Nearest Neighbors classifier Full Text Publisher DOI Details People (1) Files (1) ...

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 cybersecurity ...

The code can be found in the repository, it can be downloaded as ZIP by clicking in the geen Code button. The only necessary file is the notebook confidence.ipynb. To successfully run the notebook, ...

This project implements our Adaptive kNN-MT as well as Vanilla kNN-MT. The implementation is build upon fairseq, and heavily inspired by knn-lm, many thanks to the authors for making their code ...

Abstract: ${K}$ -nearest neighbors (KNN) algorithms are widely used for indoor fingerprint positioning, but conventional KNN algorithms usually adopt received signal strength (RSS) similarity as a ...

Hence, the server does not need to update the query results unless the query moves out of its safe region. Previous work uses Time-Parameterized kNN (TPkNN) queries to construct the safe region.