Customer segmentation using K-Means clustering to classify customers into different groups based on their characteristics. The goal is to help businesses personalize marketing strategies and improve ...

Currently, a wide array of clustering algorithms have emerged, yet many approaches rely on K-means to detect clusters. However, K-means is highly sensitive to the selection of the initial cluster ...

NEW YORK — I conducted a quick poll among Yankees fans I know, asking what they thought about manager Aaron Boone’s decision to pull Clarke Schmidt after seven innings of no-hitter against the ...

Cloud elasticity involves timely provisioning and de-provisioning of computing resources and adjusting resources size to meet the dynamic workload demand. This requires fast, and accurate resource ...

Based on several lines of interesting data, the authors conclude that FMRP, though associated with stalled ribosomes, does not determine the position on the mRNAs at which ribosomes stall. Although ...

Seabed-origin oil spills pose distinct challenges in marine pollution management due to their complex transport dynamics and ...

Clarko’s cluster 2.0? How the Roos have evolved and what it means for the 2025 draft No one noticed Alastair Clarkson’s recent coaching masterstroke but it may well ensure North’s draft ...

As a result, they found that ESO 280-SC06 is a tidally disrupted cluster that was once massive but has lost at least 95% of its initial mass. The new findings were published June 18 on the arXiv ...

Clustering was performed with two different loss functions - Loss = KL-Divergence(soft assignment distribution, target distribution) + Autoencoder Reconstruction loss , where the target distribution ...