The article titled "A Practical Evaluation of AutoML Tools for Binary, Multiclass, and Multilabel Classification" by Marcelo V. C. Aragão et al. provides a comprehensive analysis of various Automated Machine Learning (AutoML) frameworks. Here’s a sum...
Abstract Short texts generated by individuals in online environments can provide social and behavioral scientists with rich insights into these individuals’ internal states. Trained manual coders can reliably interpret expressions of such internal st...
Abstract Social media platforms have made increasing use of irony in recent years. Users can express their ironic thoughts with audio, video, and images attached to text content. When you use irony, you are making fun of a situation or trying to make...
Abstract :This is Part II of the two-part comprehensive survey devoted to a computing framework most commonly known under the names Hyperdimensional Computing and Vector Symbolic Architectures (HDC/VSA). Both names refer to a family of computational ...
Abstract:This two-part comprehensive survey is devoted to a computing framework most commonly known under the names Hyperdimensional Computing and Vector Symbolic Architectures (HDC/VSA). Both names refer to a family of computational models that use ...
Abstract: The emergence of big data and computational tools has introduced new possibilities for using large-scale textual sources in sociological research. Recent work in sociology of culture, science, and economic sociology has shown how computatio...
"all models of language are wrong but some are useful" "Once the research question is defined and the researcher is performing measurement, we can assess how accurate a method is at recovering the specific concept of interest to the researcher. Becau...
Summary The study proposes a framework that combines machine learning techniques and explainable AI to automatically identify and interpret students’ learning styles within a virtual learning environment (VLE). Since students often exhibit multiple l...
Abstract: Stochastic processes are regarded as a dynamic component of probability theory. By understanding the theory of stochastic processes, people can investigate random phenomena under a given tim