This paper presents an open-source implementation of PL-kNN, a parameterless version of the k-Nearest Neighbors algorithm. The proposed model, developed in Python 3.6, was designed to avoid the choice ...

This repository contains a Python package that implements the k-Nearest Neighbors (k-NN) algorithm for classifying Iris flowers into three species: setosa, versicolor, and virginica. The package uses ...

This study implements the K-Nearest Neighbors (K-NN) algorithm for classification tasks using the Python programming language in both serial and parallel modes.

The k-nearest neighbors (KNN) algorithm is a simple, easy-to-implement supervised machine learning algorithm that can be used to solve both classification and regression problems.

To solve the problem, the missing data should be estimated as accurately as possible. In this paper, a k-nearest neighbor based missing data estimation algorithm is proposed based on the temporal and ...