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.
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Updated
Feb 4, 2023 - R
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.
This project was in collaboration with University Hospital Birmingham
Trabajo Especialización 2018 (ALR)
Research project to measure the firm Expected Investment Growth (EIG) based on a combination of machine learning tools and text regression.
Understand what influences bike rental usage. 🚲
A web application implementing models to predict ICU admission for COVID-19 patients based on clinical, laboratory and imaging parameters
Learners for the `mlexperiments` R 📦
Multivariate linear regression, CART and Random Forest dataset analysis
The MCB for variable selection identifies two nested models (upper and lower confidence bound models) containing the true model at a given confidence level.
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.
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.
Scripts used to prepare the "Pathogen invasion history elucidates contemporary host pathogen dynamics" publication by Vredenburg et al. (2019)
👥 Análise de dados relacionada a predição de prejuízo funcional em sujeitos com transtornos de humor.
Fake News analysis and prediction in R Script. Naive Bayes, Random Forest, SVM, NNET, ROC, Confusion Matrix, Accuracy, F1 score.
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.
🧠 Machine learning analysis for the paper named "Predicting 3-year persistent or recurrent major depressive episode using machine learning techniques".
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