GitHub

A Computational Pipeline for Stratifying Autoimmune Patients Using Binary Antibody Data

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 ...
Frontiers

Data analysis competition: connectivity and multivariate classification approaches

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 ...
IEEE

Multivariate Time Series Classification via Heterogeneous Graph Representation

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 ...
SciELO

EVALUATION OF THE QUALITY AND CLASSIFICATION OF PARBOILED RICE USING NEAR-INFRARED SPECTROSCOPY AND MULTIVARIATE STATISTICAL ANALYSES

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 ...
C&EN

Systematic Characterization of Tea Varieties and Manufacturing Processes through Chemical Profiling and Multivariate Statistical Analysis

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 ...
GitHub

Stochastic gradient-boosted decision trees for multivariate classification, usable standalone and via Python interface.

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 ...
SciELO

Discrimination between COVID-19 Positive and Negative Blood Sera Using an Unmodified Disposable Impedimetric Sensor and Multivariate Analysis

The present study introduces a direct approach for classifying blood serum samples as either positive or negative for coronavirus disease (COVID-19) by associating the electrochemical impedance data ...