My Master Degree Project

R-based mental-health analytics project featuring data prep, exploratory analysis, GLM/decision-tree models, and ROC/AUC evaluation in a reproducible workflow.

Results of binary classification of Yelp reviews as pertaining to conventional or alternative medicine using random forests

Built a logistic regression model and a classification tree model for predicting the final status of a loan based on various variables available. Confusion matrix and misclassification rate for each model for a test dataset. Variables that appear to be important for predicting outcome. Plotted and described the ROC curves and AUC for the four mo…

mewto is an R package that allows you to experiment with different thresholds for classification of prediction results in the case of binary classification problems and visualize various model evaluation metrics, confusion matrices and the ROC curve. It also allows you to calculate the optimal threshold based on a weighted evaluation criterion.

Default-Risk Prediction & Screening at Loan Origination in P2P Consumer Lending, with a Double Machine Learning Extension of the Effects of Longer Terms and High Interest Rates

Reprodução e aprimoramento metodológico de um estudo de predição de colelitíase usando Machine Learning em R, com seleção de variáveis, validação cruzada repetida, otimização de threshold e ensemble RF + XGBoost.

Estimate the receiver operating characteristic (ROC) curve, area under the curve (AUC) and optimal cut-off points for individual classification with complex survey data.

You can find exercises and codes realized during this lecture

Naive Bayes, Confusion Matrix, and ROC Analysis were conducted using R to determine how different variables lead to a customer of a bank taking out a personal bank loan.

Complete package for all Data Science models using R. Starting form Preprocessing, Data Manipulation, Feature Engineering, Model Building, and Model Validation.

Data Science (Data preprocessing) along with machine learning where patients with digestive and kidney diseases are predicted using(kNN, Naïve Bayes , and Random Forest) classifiers in R Programming Language

This repository contain scripts for ML, single-cell, and proteomics identification of critical regulators of immune cell infiltration and microglia-mediated neuroinflammation following TBI.

R Shiny App to determine the factors that are most influential in patients’ survival of CHD. I created a Logistic Regression model in R using RStudio to predict the survival of CHD patients. Retrieved the data from the PHIS database using SQL & built tableau dashboards. The model predicted the survival of CHD with an AUC of over .90 and indicate…

Hormone Therapy Decision Support System for Breast Cancer

ROC-GLM for DataSHIELD

Shiny app for generation of ROC curves

Clustering validation with ROC Curves

Evaluation of Binary Classifiers

R Code and synthetic data accompanying the paper "Identifying patients using antidepressants for the treatment of depression"