A tool for visualizing the coefficients of various regression models, taking into account empirical data distributions.
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Updated
Jul 16, 2024 - R
A tool for visualizing the coefficients of various regression models, taking into account empirical data distributions.
Survival learners for the `mlexperiments` R 📦
Learners for the `mlexperiments` R 📦
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.
Análisis de salario obtenido del paquete ISLR
we fit various splines to model the COVID-19 daily positive case numbers in Florida from 3/3/20 – 3/7/21.
Code of the least angle regression solution path by hand for an example( p=5). Then we compute the solution path for a dataset and compare it with the LASSO path.
Fake News analysis and prediction in R Script. Naive Bayes, Random Forest, SVM, NNET, ROC, Confusion Matrix, Accuracy, F1 score.
Research project to measure the firm Expected Investment Growth (EIG) based on a combination of machine learning tools and text regression.
A web application implementing models to predict ICU admission for COVID-19 patients based on clinical, laboratory and imaging parameters
The MCB for variable selection identifies two nested models (upper and lower confidence bound models) containing the true model at a given confidence level.
LASSO, elastic net, Adaptive LASSO, SCAD methods for determining top predictors for each method
Multivariate linear regression, CART and Random Forest dataset analysis
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