Abstract: Optimizing the K value in the K-Nearest Neighbor (KNN) algorithm is a critical step in enhancing model performance, particularly for tasks related to classification and prediction. The Elbow ...
ABSTRACT: Cardiovascular diseases (CVDs) are the leading cause of death worldwide, accounting for millions of deaths each year according to the World Health Organization (WHO). Early detection of ...
Abstract: The K-Nearest Neighbors (kNN) algorithm, a cornerstone of supervised learning, relies on similarity measures constrained by real-number-based distance metrics. A critical limitation of ...
Introduction: The health status of bearings is an essential prerequisite to ensure the safe and stable operation of vehicles. However, the negative impact of covariate shifts among data channels on ...
Introduction: The development of science and technology has driven rapid changes in the social environment, especially the rise of the big data environment, which has greatly increased the speed at ...
Dr. James McCaffrey of Microsoft Research presents a full demo of k-nearest neighbors classification on mixed numeric and categorical data. Compared to other classification techniques, k-NN is easy to ...
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 scenarios.
ABSTRACT: An aerial photographic coverage acquired on two consecutive days in October 2021 with a ground resolution of 20 cm and a spectral resolution of 4 bands (red, green, blue and near infrared), ...
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