TMCnet

Data Normalization vs. Standardization: What's the Difference and When to Use Each

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...
AHA/ASA Journals

Multistage Electrocardiographic Profiling for Mental Stress-Induced Myocardial Ischemia in Women: A Prospective, Age-Matched Cohort Study in China

BACKGROUND: Mental stress-induced myocardial ischemia is often clinically silent and associated with increased cardiovascular risk, particularly in women. Conventional ECG-based detection is limited, ...
IEEE

A Topological-Indicators-Based k-Means Clustering Algorithm and Its Application in Time Series Data: A Case Study on Sea Level Variability in Peninsular Malaysia

Abstract: Traditional k-means clustering is widely used to analyze regional and temporal variations in time series data, such as sea levels. However, its accuracy can be affected by limitations, ...
Mashable

TikTok deal adds new U.S. owners. Here's what this means for users.

TikTok will officially remain in the U.S. for the foreseeable future. A new, majority U.S.-owned company had been established to continue running the popular video-sharing app in the country, and has ...
Morningstar

Insulet Announces FDA 510(k) Clearance of Omnipod® 5 Algorithm Enhancements that Redefine Insulin Delivery and Simplify the Pod Experience

New 100 mg/dL Target Glucose setting offers more customization and tighter glucose management. Enhanced algorithm helps users remain in Automated Mode to improve the user experience. Most requested ...
Visual Studio Magazine

Anomaly Detection Using K-Means Clustering with JavaScript

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, ...
Scientific Research Publishing

Wang, Q., Wang, C., Feng, Z. Y. et al. (2012). Survey of K-Means Clustering Algorithm Research. Electronic Design Engineering, 20, 21-24. (In Chinese)

ABSTRACT: From the perspective of student consumption behavior, a data-driven framework for screening student loan eligibility was developed using K-means clustering analysis and decision tree models.
techannouncer

Downloadable LeetCode Python PDF: Essential Solutions and Practice

So, you’re looking to get better at coding with Python, and maybe you’ve heard about LeetCode. It’s a pretty popular place to practice coding problems, especially if you’re aiming for tech jobs.
The New York Times

Calley Means, a Kennedy Adviser, Has Left the White House

Mr. Means quietly departed his federal role about a month ago. His sister has been nominated for surgeon general. By Benjamin Mueller Calley Means, an influential adviser to Health Secretary Robert F.
Frontiers

Efficient vegetation filtering method using K-means clustering algorithm: case study of high steep rock slope

In this study, the number of clusters K for the K-means algorithm was empirically set to 6, which aligns with the expected classification of surface features into categories such as low vegetation, ...
IEEE

Research on Improved k-Means Clustering Algorithm Based on Density-Weighted Canopy

Abstract: This paper proposes an improved K-means clustering algorithm based on density-weighted Canopy to address the efficiency bottlenecks and clustering accuracy issues commonly encountered by ...