The final, formatted version of the article will be published soon. This study investigates the trading behaviors of Malaysian derivatives traders using a comprehensive dataset from Bursa Malaysia ...
A new artificial intelligence (AI) tool could make it much easier-and cheaper-for doctors and researchers to train medical imaging software, even when only a small number of patient scans are ...
This project aims to perform customer segmentation based on their annual income and spending score. Using the K-means clustering algorithm, the customers are grouped into clusters based on ...
ABSTRACT: Clustering is an unsupervised machine learning technique used to organize unlabeled data into groups based on similarity. This paper applies the K-means and Fuzzy C-means clustering ...
ABSTRACT: Clustering is an unsupervised machine learning technique used to organize unlabeled data into groups based on similarity. This paper applies the K-means and Fuzzy C-means clustering ...
Microsoft Deployment Toolkit is designed to streamline the deployment of Windows operating systems, applications, and configurations across multiple devices. If you want to capture Windows Image using ...
Abstract: K-means clustering is an unsupervised learning algorithm that assigns unlabeled data to different clusters depending on the similarity rather than predefined labels. It finds application in ...
Customer Segmentation is the process of division of customer base into several groups of individuals that share a similarity in different ways that are relevant to marketing such as gender, age, ...
Abstract: In this study, a novel clustering methodology is proposed, which utilizes k-means sequentially for performing feature reduction, segmentation, and clustering on hyperspectral imagery, to ...
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