Trained on data from NASA's exoplanet-hunting missions, the open-source ExoMiner++ deep learning model uses an advanced ...

Traditional machine learning algorithms for classification tasks operate under the assumption of balanced class distributions. However, this assumption only holds in some practical scenarios. In most ...

The new law seeks to prevent retailers from ripping off consumers by using artificial intelligence and their personal data to charge them higher prices. By Tim Balk As New Yorkers scrolled, surfed and ...

Family has always been important to those working in population genetics. When Sohini Ramachandran was a postdoc, the issue of relatives in a dataset causing inaccurate results was considered a major ...

Institute for Information Systems (WIN), Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany Introduction: The analysis of discrete sequential data, such as event logs and customer ...

The Bank of England is worried that a rise in financiers’ lending to data center lending may cause an AI bubble reminiscent of the dot-com crash in the early 2000s. The Bank of England is ...

Abstract: Data stream mining is a research area that has grown enormously in recent years. The main challenge is extracting knowledge in real-time from a possibly unbounded data stream. Clustering, a ...

ABSTRACT: Doping is an issue associated with elite sports as athletes attempt to enhance their performance to gain an edge over other athletes. However, the prevalence of doping is continuously ...

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The ML Algorithm Selector is an interactive desktop application built with Python and Tkinter. It guides users through a decision-making process to identify suitable machine learning algorithms for ...