In this assignment, kNN algorithm is implemented without using any library function. The code is tested on the iris.data dataset. Purpose. kNN is a widely used intuitive algorithm in the machine ...

This project explores three fundamental machine learning algorithms: Principal Component Analysis (PCA), K-Nearest Neighbors (KNN), and Gaussian Mixture Models (GMM). Each algorithm is presented with ...

KNN which stands for K-Nearest Neighbours is a simple algorithm that is used for classification and regression problems in Machine Learning. KNN is also non-parametric which means the algorithm does ...

SVM and kNN exemplify several important trade-offs in machine learning (ML). SVM is often less computationally demanding than kNN and is easier to interpret, but it can identify only a limited set ...

K-nearest neighbor (KNN) algorithm is a simple and widely used classification method in machine learning. This algorithm tries to search every object in the dataset to find the nearest several ...