Pūkeko use sound elements to create calls and combine them to create complex call sequences in order to expand the range of options for expressing themselves – these are the findings of an ...

Dr. James McCaffrey presents a complete end-to-end demonstration of anomaly detection using k-means data clustering, implemented with JavaScript. Compared to other anomaly detection techniques, ...

Graduate School of Economics, The University of Osaka, Osaka, Japan. Stock returns exhibit nonlinear dynamics and volatility clustering. It is well known that we cannot forecast the movements of stock ...

Singapore-based AI startup Sapient Intelligence has developed a new AI architecture that can match, and in some cases vastly outperform, large language models (LLMs) on complex reasoning tasks, all ...

Introduction: The relationship between physical activity and anxiety among students has been extensively studied, with research highlighting the protective effects of physical activity on mental ...

Hierarchical namespaces make it easier to share your cluster by making namespaces more powerful. For example, you can create additional namespaces under your team's namespace, even if you don't have ...

Autoimmune conditions and ‘breast implant illness’ in breast cancer patients with implant-based breast reconstructions. Proportions of patients with clinically meaningful symptoms by CL at Y1 (may not ...

Abstract: Fuzzy clusters, where ambiguous samples belong to multiple clusters, are common in real-world applications. Analyzing such ambiguous samples in large-scale datasets is crucial for practical ...

About every 10 minutes, it seems, a new article about a "revolutionary breakthrough" in AI hits my screen. A new approach, a new feature, billions of dollars this, AI agents that. It has been non-stop ...

K-Means is a partition-based clustering technique that aims to minimize the distance between data points and their respective cluster centroids. Hierarchical Clustering is an agglomerative approach ...