KNN is a simple and intuitive algorithm that classifies an unknown instance based on the similarity of its features to the features of its k closest neighbors in the training data. The k parameter ...

This project does not use any machine learning imports nor basic libraries like math, numpy, or pandas. The goal is to provide an extremely fundamental, step-by-step approach to understanding this ...

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 ...

In this online data science specialization, you will apply machine learning algorithms to real-world data, learn when to use which model and why, and improve the performance of your models. Beginning ...

Our proposed deep learning approach outperforms many traditional machine learning methods, such as decision tree, k-nearest neighbor algorithm (KNN), and histogram of oriented gradient (HOG) based ...

This paper compares mainly the modelling accuracy of the KNN and kriging coupling algorithm and of the kriging algorithm as well as evaluate the improved machine learning algorithm. According to ...