This project consists in the implementation of the K-Means and Mini-Batch K-Means clustering algorithms. This is not to be considered as the final and most efficient algorithm implementation as the ...
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, ...
ABSTRACT: Stock returns exhibit nonlinear dynamics and volatility clustering. It is well known that we cannot forecast the movements of stock prices under the condition that market is efficient. In ...
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: As a highly contagious respiratory disease, influenza exhibits significant spatiotemporal fluctuations in incidence, posing a persistent threat to public health and placing considerable ...
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 ...
Trump to sign executive order allowing crypto, real estate, and private equity in 401(k) retirement plans. Fiduciaries may receive updated guidance clarifying how ERISA applies to crypto in retirement ...
This project consists in the implementation of the K-Means and Mini-Batch K-Means clustering algorithms. This is not to be considered as the final and most efficient algorithm implementation as the ...
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