Identify the most important variables that contribute to the level of sustainability of schools using supervised machine learning. Use the importance to assign a weight to each characteristic and calculate a sustainability index for each school.

Final Project: Predictive and descriptive analysis, interpretations, and recommendations based on Austin Animal Center data on cats housed at the shelter. The main focus of this analysis is to determine which factors affect a cat's chances of being adopted or returned to their owner.

A large dataset for studying the early readmission of diabetic patients problem

R script to rank and select variables based on their importance/predictive power

Code for Master Thesis

Code and tutorials for implementing the GlObal And Local Score

Comprehensive dimensionality reduction and cluster analysis toolset

Creating predictive models to classify Trump's vote share and clustering counties based on demographics and economic variables. Report findings in PDF with detailed methodologies, model assessments, and R code for the project.

This project relates to a methodological report on canton Bern forest fire modelling and mitigation strategies.

Build a predictive model for the sale prices of homes in a city and explore potential equity issues with the real-estate assessment process

An R package for selecting variables in regression models

🌳 🎯 Cross Validated Decision Trees with Targeted Maximum Likelihood Estimation

💫 🎯 Automatic identification of variable and interaction importance using basis functions and non-parametric estimation of interactions/effect modification using joint stochastic interventions.

Parkinson's Progression Marker Initiative data science challenge, 2016

🎯 🎲 Targeted Learning of the Causal Effects of Stochastic Interventions

Tools to Support Relative Importance Analysis

📦 🎲 R/txshift: Efficient Estimation of the Causal Effects of Stochastic Interventions, with Corrections for Outcome-Dependent Sampling

🎯 💯 Targeted Learning and Variable Importance for the Causal Effect of an Optimal Individualized Treatment Intervention

Variable importance via oscillations