First proposed by the US Air Force School of Aviation Medicine in 1951, and having to accommodate itself to the state-of-the-art of mid-20th century computing hardware, K-Nearest Neighbors (KNN) is a ...

K-Nearest Neighbors (KNN) is a conceptually simple yet very powerful algorithm, and for those reasons, it’s one of the most popular machine learning algorithms. Let’s take a deep dive into the KNN ...

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 ...

Building k-nearest neighbor (kNN) graphs is a necessary step in such areas as data mining and machine learning. So in this paper, we attempt to study the kNN furthermore, we first propose a parallel ...

In this paper different machine learning algorithms and H20 AutoML are applied to compare the results and analysis of the Machine Learning Heart Disease dataset. ... Patients Heart Data Pair Graph.

Graph convolutional neural networks can effectively process geometric data and thus have been successfully used in point cloud data representation. However, existing graph-based methods usually adopt ...

This article explores what knowledge graphs are, why they are becoming a favourable data storage format, and discusses their potential to improve artificial intelligence and machine learning ...