This project aims to predict heart failure outcomes by applying statistical learning algorithms. The goal is to improve the prediction accuracy through the SuperLearner algorithm.
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Updated
Jun 9, 2024 - R
This project aims to predict heart failure outcomes by applying statistical learning algorithms. The goal is to improve the prediction accuracy through the SuperLearner algorithm.
Survival learners for the `mlexperiments` R 📦
A tool for visualizing the coefficients of various regression models, taking into account empirical data distributions.
The study focuses on modeling and predicting H5N1 bird flu outbreaks in the United States at the county level, utilizing diverse statistical techniques and machine learning models.
Learners for the `mlexperiments` R 📦
Code library for common machine learning algorithms
Development of new ML library
Code and writings for my internship project at the Transcriptomic Bioinformatics research group at University Medical Center Groningen.
Detailed exploratory and predictive analysis of Airbnb data using R for data manipulation and model building.
Norm Constrained Generalised Linear Model using numpy, numba and scipy.
Scripts used to prepare the "Pathogen invasion history elucidates contemporary host pathogen dynamics" publication by Vredenburg et al. (2019)
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.
: 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
🧠 Machine learning analysis for the paper named "Predicting 3-year persistent or recurrent major depressive episode using machine learning techniques".
👥 Análise de dados relacionada a predição de prejuízo funcional em sujeitos com transtornos de humor.
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