Abstract: To address the issue of sharing qualitative models between different near-infrared spectrometers, this study explores the effectiveness of calibration transfer techniques. Two different ...

Nearest neighbour classification techniques, particularly the k‐nearest neighbour (kNN) algorithm, have long been valued for their simplicity and effectiveness in pattern recognition and data ...

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 ...

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 ...

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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.

Images:- Contains all the graphs that were generated during exploratory data analysis. Data:- Contains all the data files that were utilized. These files were either outsourced from the internet or ...

ABSTRACT: Arrhythmia beat classification is an active area of research in ECG based clinical decision support systems. In this paper, Pruned Fuzzy K-nearest neighbor (PFKNN) classifier is proposed to ...

In wireless sensor networks, the missing of sensor data is inevitable due to the inherent characteristic of wireless sensor networks, and it causes many difficulties in various applications. To solve ...