Scientists in Iraq used a k-Nearest Neighbors algorithm to evaluate the operational status of PV modules under various conditions, including partial shading, open circuit, and short circuit ...

Dr. James McCaffrey presents a complete end-to-end demonstration of k-nearest neighbors regression using JavaScript. There are many machine learning regression techniques, but k-nearest neighbors is ...

Unbeatable baseline: Nearest-neighbor algorithm. Often, when you are trying to write a paper, you want to show that “your cuve is better than my curve”.

The weighted k-nearest neighbors (k-NN) classification algorithm is a relatively simple technique to predict the class of an item based on two or more numeric predictor variables. For example, you ...

But the logic to convert gesture to control signals is all Vectron, and uses a k -nearest neighbor algorithm executed in 6502 assembly.

One simple illustration is K-nearest neighbor algorithm used for classification. It can be applied to digitizing hand-written characters, detecting hidden packages, etc. But here is a way of how ...

Robust covariance estimation commonly proceeds by downweighting outliers. In this article we measure the "outlyingness" of a data point by the standardized distance between the point and its Kth ...

With the flaw corrected, the issues surrounding interpretation of the nearest-neighbor statistic are discussed, and a review is made of the special difficulties of applying the technique to ...