A python port of the glmnet package for fitting generalized linear models via penalized maximum likelihood.

• Updated Jul 24, 2024
• Python

Utilities for glmnet

• Updated Sep 10, 2023
• R

Accurate estimation and robust modelling of translation dynamics at codon resolution

• Updated Jun 27, 2017
• Python

glmnet for python

• Updated Mar 30, 2017
• Python

Leap motion image recognition gesture checker GUI(C#) for developing Hand bone angles, Positions, and recognizable gestures(fuzzy logic) implementable in Virtual/Augmented reality apps.

• Updated Oct 16, 2021
• C#

Calculating Regularized Adjusted Plus-Minus (RAPM) with R

• Updated Aug 25, 2020
• HTML

: a R pipeline to identify the most important predictor qualitative and quantitative variables for discrimination of your variable of interest like genotype or sex or response to treatment by using phenotypic or clinical data from different diseases

• Updated Aug 17, 2022
• R

MVPA tutorial - Rogers lab brain imaging unit

• Updated Mar 24, 2017
• MATLAB

glmnet compiled for MATLAB R2020, Windows 10 64-bit

• Updated Jul 11, 2025
• Fortran

Survival learners for the `mlexperiments` R 📦

• Updated Oct 16, 2025
• R

Algorithmes d’apprentissage et modèles statistiques: Un exemple de régression logistique régularisée et de validation croisée pour prédire le décrochage scolaire

• Updated Jun 11, 2021
• Jupyter Notebook

Norm Constrained Generalised Linear Model using numpy, numba and scipy.

• Updated Jul 6, 2023
• Python

• Updated Nov 27, 2020
• R

Advanced Regression Techniques to predict housing prices.

• Updated Mar 28, 2017
• R

stress detection in social networks

• Updated Nov 10, 2019
• R

Learners for the `mlexperiments` R 📦

• Updated Oct 16, 2025
• R

Code library for common machine learning algorithms

• Updated Jul 15, 2024
• Python

The MCB for variable selection identifies two nested models (upper and lower confidence bound models) containing the true model at a given confidence level.

• Updated Aug 29, 2020
• R

A tool for visualizing the coefficients of various regression models, taking into account empirical data distributions.

• Updated Jan 14, 2025
• R

My role in this group project was to perform regression analysis on quarterly financial data to predict a company's market capitalization. I used R to develop ordinary least squares (OLS), stepwise, ridge, lasso, relaxed lasso, and elastic net regression models. I first used stepwise and OLS regression to develop a model and examine its residual...

• Updated Jun 29, 2021