ABSTRACT: Cybersecurity has emerged as a global concern, amplified by the rapid expansion of IoT devices and the growing digitization of systems. In this context, traditional security solutions such ...

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 ...

Eggplant seed vigor is a crucial indicator of its germination rate and seedling growth quality. In response to the need for efficient and nondestructive assessment methods, this study explores the use ...

Introduction: Integrating immune repertoire sequencing data with single cell sequencing data offers profound insights into the diversity of immune cells and their dynamic changes across various ...

Diabetes Prediction is my weekend practice project. In this I used KNN Neighbors Classifier to trained model that is used to predict the positive or negative result. Given set of inputs are BMI(Body ...

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 ...