Sparse logistic regression (SLR), which is widely used for classification and feature selection in many fields, such as neural networks, deep learning, and bioinformatics, is the classical logistic ...

1 INTRODUCTION The main goal of this paper is to develop a credible dynamic model of the multiple trailers on a tractor system for the production logistics application i.e. logistic train. This ...

These insights could help scientists build models that are simpler, more efficient, and possibly more transparent. More information: Vittorio Erba et al, Bilinear Sequence Regression: A Model for ...

Analysis of 2023 BRFSS data exploring the relationship between insurance status, flu shot uptake, and preventive care access. Includes data cleaning, EDA, logistic regression, and visualizations using ...

In order to reduce the calculation cost and improve the robustness of appearance model, this paper presents an optimal object tracking method that consists of improved inverse sparse representation ...

A MCMC Bayesian analysis versus Frequentist Analysis of Animal Crossing: New Horizons game players in-game behavior using a Multinomial Logistic Regression Model to adjust the original paper results.