**In this study, we implemented and evaluated the K-Nearest Neighbors (KNN) algorithm from scratch, applying it to three distinct datasets: Breast Cancer, Car Evaluation, and Hayes-Roth, sourced from ...

Welcome to the K-Nearest Neighbors (KNN) Classifier project! This implementation allows for efficient classification of data with 7 parameters. Each data point has an associated class to predict, ...

Rather, the model is constructed entirely from the provided data. Second, there is no splitting of the dataset into training and test sets when using KNN. KNN makes no generalizations between a ...

This paper studies KNN algorithm and analyzes the factors that affect the accuracy of image classification. Then the algorithm is improved by optimizing the selection strategy of K value in ...

KNN algorithm is particularly sensitive to outliers and noise contained in the training data set. In this paper, we use the reverse cloud algorithm to map the training samples into clouds. Each ...