Why marketing mix modeling is still hard to get right

Open-source tools have made MMM more accessible, but reliable results still depend on clean data, thoughtful modeling, and ...
The Durango Herald

Local journalism begins with you, our readers.

As we adjust our print schedule, launch a new website and rely on the U.S. Postal Service for delivery, please know these changes were not made lightly. They were made with our readers in mind — and ...
GitHub

c-lasso: a Python package for constrained sparse regression and classification

c-lasso is a Python package that enables sparse and robust linear regression and classification with linear equality constraints on the model parameters. For detailed info, one can check the ...
The Lancet

Accurate classification of pulmonary nodules by a combined model of clinical, imaging, and cell-free DNA methylation biomarkers: a model development and external validation study

cDepartment of Radiology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China dDepartment of Radiation Oncology, The First Affiliated Hospital of Guangzhou Medical ...
Frontiers

Causative Classification of Ischemic Stroke by the Machine Learning Algorithm Random Forests

Prognosis, recurrence rate, and secondary prevention strategies differ by different etiologies in acute ischemic stroke. However, identifying its cause is challenging. We retrospectively reviewed the ...
GitHub

transforEmotion: Sentiment Analysis for Text, Image and Video Using Transformer Models

With transforEmotion you can use cutting-edge transformer models for zero-shot emotion classification of text, image, and video in R — without the need for a GPU, subscriptions, or paid services, and ...
Frontiers

tascCODA: Bayesian Tree-Aggregated Analysis of Compositional Amplicon and Single-Cell Data

tascCODA posits a Dirichlet-Multinomial model for Y i,⋅ for each sample i ∈ 1…, n, thus accounting for the compositional nature of the count data. The covariates are associated with the features ...
Michigan Technological University

Geoinformatics—Graduate Certificate

Meet the demand for geospatial professionals and big data analytics experts. Develop knowledge and skills in geospatial data analytics and information science. Explore environmental geoscience, ...