If you are interested in machine learning, you might have encountered two popular algorithms: KNN and K-means. Both of them are based on the idea of finding similarities among data points, but ...

k-Nearest Neighbour is the most simple machine ... of k-NN algorithm is that it's simple to implement and understand. It is lazy learning algorithm and therefore requires no training prior to making ...

this paper proposes an adaptive ensemble algorithm called Adaptive Fusion-KNN, based on KNN. AF-KNN integrates two weak classifiers based on KNN and utilizes machine learning methods to adaptively ...

In this study, colors are classified by using K-Neares Neşghbor Machine Learning ... Algorithm K nearest neighbors is a simple algorithm that stores all available cases and classifies new cases based ...

Given a new image of a concrete structure, use the trained KNN model to predict the length of the cracks. The supervised learning algorithm Support Vector Machine (SVM), which is utilized for ...

At low feature levels, the SVM is two-dimensional (image above), but ... is a lean algorithm that still features prominently across academic papers and private sector machine learning research ...

Other use cases are being explored, ranging from image generation ... look at how machine learning works, followed by a short guide to implementing and training a machine learning algorithm.