Code and data processing scripts for the proof of concept bianry data pipeline analysis of autoantibody profiles in Sjögren’s syndrome and rheumatoid arthritis (synthetic dataset, N=176). Figures ...
While there are a number of advanced data analysis techniques that allow us to embrace distributed electrophysiological activity measured by MEG, these tools are somewhat underexploited. This includes ...
Multivariate time series (MTS) classification is essential in industries, such as healthcare and manufacturing, where it helps extract key features from complex data for decision-making and ...
Physical classification is the official standard method for determining grain quality for commercialization. However, it is a time-consuming, subjective operation, susceptible to errors, and requires ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. The extensive diversity of tea, resulting from varietal traits and manufacturing ...
Check the paper on ArXiv: FastBDT: A speed-optimized and cache-friendly implementation of stochastic gradient-boosted decision trees for multivariate classification Stochastic gradient-boosted ...
Abstract: Multivariate Time Series (MTS) classification is a critical yet challenging task in the field of data mining. Recently, Graph Neural Networks (GNNs) have emerged as powerful tools for this ...
The West Virginia Secondary School Activities Commission (WVSSAC) has released its updated regional and class alignments for all high school sports, effective for the 2025-26 and 2026-27 academic ...
ABSTRACT: The rapid growth of unlabeled time-series data in domains such as wireless communications, radar, biomedical engineering, and the Internet of Things (IoT) has driven advancements in ...
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