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

Utilities for glmnet

Accurate estimation and robust modelling of translation dynamics at codon resolution

glmnet for 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.

Calculating Regularized Adjusted Plus-Minus (RAPM) with R

: 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

MVPA tutorial - Rogers lab brain imaging unit

glmnet compiled for MATLAB R2020, Windows 10 64-bit

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

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

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

Survival learners for the `mlexperiments` R 📦

stress detection in social networks

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…

Advanced Regression Techniques to predict housing prices.

Code library for common machine learning algorithms

Detailed exploratory and predictive analysis of Airbnb data using R for data manipulation and model building.

Comparison between the implementations of the Lasso algorithm between the Spark MLib library and the R glmnet package.