Accuracy, calibration stability, and general robustness have been persistent challenges for non-invasive glucose monitoring. (3−5) Chemometrics and machine learning algorithms are generally used to ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression using JavaScript. Linear regression is ...

Multivariate time series data, which has more complex and multidimensional characteristics compared to univariate data, is used in fields such as urban transportation, power grids, and financial ...

A multivariable logistic regression analysis was conducted to model variables with the highest predictive value for severe COVID-19. Variables for the model were selected based on review of the ...

Land use regression (LUR) models have been used to assess air pollutant exposure, but limited evidence exists on whether location-specific LUR models are applicable to other locations (transferability ...

Motivated by modeling a general behavioral function of a target system, a data-driven multivariable support vector regression (SVR) is developed. The multivariable SVR is sought to estimate a ...

According to the model obtained from the multivariate logistic regression analysis, a prediction formula is established, and the prediction probability and prediction grouping of each case are ...

statistics linear-regression magnetotellurics multivariate-regression multivariate-analysis multivariate-statistics magnetotelluric robust-statistics Updated on May 15 C++ ...

numpy linear-regression scikit-learn pandas seaborn multivariate-analysis lags mae correlation-analysis matplotlib-pyplot univariate-analysis Updated 1 minute ago Jupyter Notebook ...