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, ...

As the Trump administration has put housing affordability in the spotlight recently, one of the president’s top economic advisors unveiled how Americans might be able to use 401(k) funds for a home ...

Lucas is a writer and narrative designer from Argentina with over 15 years of experience writing for games and news. He keeps a watchful eye at the gaming world and loves to write about the hottest ...

Our goal at The Upshot is to produce distinctive explanatory journalism. But how do we get there? Some of our best work starts with a reporter squinting at a table, or a list, or a rough chart, and ...

The Bureau of Economic Analysis released its personal consumption expenditures price index data for September earlier today. Here is the report, at a glance: Core YoY: 2.8% increase, in line with ...

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, ...

Chase is back with one of its more lucrative credit card promotions for Apple shoppers. Starting today and running until December 7, your Chase Ultimate Rewards points are worth up to 50% when ...

The rise of artificial intelligence is driving a surge of data center construction across the United States, and rural communities are feeling the impact. Reading time 4 minutes Elena Schlossberg and ...

Americans are increasingly diverging in their spending, with wealthier shoppers flexing their purchasing power while lower-income customers start to pull back. Sectors like food, automotives and ...

Rocky high steep slopes are among the most dangerous disaster-causing geological bodies in large-scale engineering projects, like water conservancy and hydropower projects, railway tunnels, and metal ...

Abstract: 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 ...

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 ...