This paper formally analyses the effect of normalisation yielding results significantly far from the state-of-the-art traditional claims.

Both metrics enable the automatic selection of the most appropriate normalisation method for a particular engineering problem, which can significantly improve ...

Both metrics enable the automatic selection of the most appropriate normalisation method for a particular engineering problem, which can significantly improve ...

Influence of statistical feature normalisation methods on K-Nearest Neighbours and K-Means in the context of industry 4.0. https://doi.org/10.1016/j.engappai ...

Both metrics enable the automatic selection of the most appropriate normalisation method for a particular engineering problem, which can significantly improve ...

Influence of statistical feature normalisation methods on K-Nearest Neighbours and K-Means in the context of industry 4.0. Overview of attention for article ...

Influence of statistical feature normalisation methods on K-Nearest Neighbours and K-Means in the context of industry 4.0. Niño-Adan, I. Landa-Torres, I.

Influence of statistical feature normalisation methods on K-Nearest Neighbours and K-Means in the context of industry 4.0. Article. May 2022; ENG APPL ARTIF ...

Methods for scaling such as Z-score normalization and Min-Max scaling are used to assign uniform weights to features for scale variant distance metrics.

Oct 23, 2024 · This paper presents a novel framework for implementing the k-NN algorithm, designed to enhance its accuracy in contexts with sparse data.