Utilities for glmnet

: 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

Survival learners for the `mlexperiments` R 📦

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

stress detection in social networks

Advanced Regression Techniques to predict housing prices.

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

This project was in collaboration with University Hospital Birmingham

Research project to measure the firm Expected Investment Growth (EIG) based on a combination of machine learning tools and text regression.

Learners for the `mlexperiments` R 📦

Elastic Net, Lasso and Ridge models can be analyzed by the formula format.

We use machine learning techniques for identification of the best cognitive markers for cocaine dependence.

we fit various splines to model the COVID-19 daily positive case numbers in Florida from 3/3/20 – 3/7/21.

A multi-response Gaussian model capable of accurately estimating the composition of blood samples from their gene expression profiles. Fit on Affymetrix Gene ST gene expression profiles using the glmnet R package.

Feature Selection using Elastic net function in the glmnet R package

Fake News analysis and prediction in R Script. Naive Bayes, Random Forest, SVM, NNET, ROC, Confusion Matrix, Accuracy, F1 score.

🧠 Machine learning analysis for the paper named "Predicting 3-year persistent or recurrent major depressive episode using machine learning techniques".

Sample data of Indian Domestic flights operated between march and june of 2019 was explored. Machine learning models that predicts the cost of the ticket was built.

Trabajo Especialización 2018 (ALR)