Individual sensor systems have limitations in the complex task of classifying shredded tobacco. This study aims to overcome these limitations by developing a novel evolutionary algorithm-based feature ...

SmartKNN is a nearest-neighbor–based learning method that belongs to the broader KNN family of algorithms.

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: Accurate prediction of malaria incidence is indispensable in helping policy makers and decision makers intervene before the onset of an outbreak and potentially save lives. Various ...

ABSTRACT: This study addresses the growing demand for news text classification driven by the rapid expansion of internet information by proposing a classification algorithm based on a Bidirectional ...

Quantum computing has become a breakthrough in many different research and applied areas. As various authors have demonstrated, the quantum properties have made some computational processes parallel ...

Abstract: K-nearest neighbor classification algorithm can quickly deal with the classification problem in this paper, but when calculating the similarity, it will assign the same weight to all ...

Abstract: Machine learning is about prediction on unseen data or testing data and a set of algorithms are required to perform task on machine learning. There are three types of machine learning are ...