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In forecasting economic time series, statistical models often need to be complemented with a process to impose various constraints in a smooth manner. Systematically imposing constraints and retaining ...

An end-to-end machine learning project to predict Autism Spectrum Disorder (ASD) risk in adults. Features a full ETL pipeline, comparative analysis of unsupervised & supervised models, and a final ...

Getting input from users is one of the first skills every Python programmer learns. Whether you’re building a console app, validating numeric data, or collecting values in a GUI, Python’s input() ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. We present a spin-adapted coupled cluster singles and doubles model for the excitation ...

1 Clinical Laboratory, Dongyang People’s Hospital, Dongyang, Zhejiang, China 2 Clinical Laboratory, The Second People’s Hospital of Yuhuan City, Yuhuan, Zhejiang, China Introduction: In this study, we ...

Ukraine has tested long-range FPV drones with fiber optic control. State defense technology cluster Brave1 reported on this. The test, organized by Brave1 with the support of the Deputy ...

ABSTRACT: The use of machine learning algorithms to identify characteristics in Distributed Denial of Service (DDoS) attacks has emerged as a powerful approach in cybersecurity. DDoS attacks, which ...

Abstract: K-means is a commonly used algorithm in machine learning. It is an unsupervised learning algorithm. It is regularly used for data clustering. Only the number of clusters are needed to be ...

Abstract: The clustering algorithm is a popular lightning data processing method. Traditional density-based algorithm can't function without input of initial parameter Min_ρ or neighborhood radius ε.