Bayesian network analysis in R
-
Updated
Sep 6, 2024 - R
Bayesian network analysis in R
4 Plotly Dash apps that animate Bayesian updates of 3-dimensional Dirichlet distributions with multinomial data
GEE solver for correlated nominal or ordinal multinomial responses using a local odds ratios parameterization.
Simulates correlated multinomial responses conditional on a marginal model specification.
This project aims to predict lung cancer using Multiple Linear Regression and Logistic Regression algorithms. By analyzing various factors, such as patient demographics, lifestyle habits, and medical history, the algorithms predict the likelihood of a patient developing lung cancer.
Hurdle Distributed Multinomial Regression (HDMR) implemented in Julia
Distributed MCMC Inference in Dirichlet Process Mixture Models (High Performance Machine Learning Workshop 2019)
Multinomial sampler for Perl
EDA and model fitting for Forest Cover Type Prediction Kaggle Competition. Final results around the 69th percentile (top 31%).
Binary and multinomial probit regression using I-priors
My PhD thesis: Regression modelling using priors depending on Fisher information covariance kernels (I-priors)
Example of Supervised Machine Learning (Multinomial Classification) using XGBoost and Shapley Value in Python
Overdispersion Models (OM) using Generalized Estimating Equations (GEE)
Course by Jacob O. Wobbrock
Modelling and Analysis of the public datasets from St. Paul
Multinomial classification tasks in Reddit
Text Category Classifier
Add a description, image, and links to the multinomial topic page so that developers can more easily learn about it.
To associate your repository with the multinomial topic, visit your repo's landing page and select "manage topics."