Abstract: The density peaks clustering (DPC) algorithm is a density-based clustering method that effectively identifies clusters with uniform densities. However, if the datasets have uneven density, ...

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 most ...

Abstract: We present a direct (noniterative) algorithm for 1-D quadratic data fitting with neighboring intensity differences penalized by the Huber function. Applications of such an algorithm include ...

Graclus (latest: Version 1.2) is a fast graph clustering software that computes normalized cut and ratio association for a given undirected graph without any eigenvector computation. This is possible ...

Nick is a freelance writer from Chicago, IL, with a BA in Creative Writing from the University of Illinois at Urbana-Champaign. His lifelong belief in the artistic power of video games led him to ...

University of Bremen, Institute for Physical and Theoretical Chemistry, Leobener Str. 6, D-28359 Bremen, Germany Bremen Center for Computational Materials Science, University of Bremen, Am Fallturm 1, ...

1 Facultad de Ingeniería, Universidad Andres Bello, Santiago, Chile. 2 Department of Mining Engineering, Universidad de Chile, Santiago, Chile. 3 Advanced Mining Technology Center, Universidad de ...

Machine learning algorithms, a subfield of artificial intelligence (AI) —is revolutionizing industries with the aid of permitting systems to examine information and improve their performance without ...

Clustering methods in Machine Learning includes both theory and python code of each algorithm. Algorithms include K Mean, K Mode, Hierarchical, DB Scan and Gaussian Mixture Model GMM. Interview ...