The goal of this project was to build a machine learning model capable of accurately predicting depression in a population where the incidence rate is 15%.

The goal of this project is to develop and evaluate machine learning models that predict heart disease in individuals based on the available features.

This third prostate cancer project will provide an alternate logistical challenge by presenting a highly imbalanced dataset with significant overlap in category predictions. I predict the outcomes based on the comparisons of Project 1 and Project 2 and then compare the results to these predictions.

This project simulated a prostate cancer screening test to evaluate how varying thresholds impact the ability of the model to correctly classify clinically significant prostate cancer.

ROC-GLM and calibration analysis for DataSHIELD

Mithilfe von Machine Learning und Open Data zu Unfällen in Berlin (2018-2021) beantworten wir folgende Frage: Was sind die wichtigen Faktoren/Einflüsse auf Unfallgefahr? Und wie gut lässt sich damit die Unfallschwere überhaupt vorhersagen?

R package 'wROC'. Estimation of the ROC curve and AUC with complex survey data.

Car insurance prediction using Logistic Regression and the Naive Bayes

PyCaret: Simplifying machine learning workflows with a low-code, open-source Python library.

This project employs XGBoost regression and XGBoost classifier model to predict user order and user churn on online travel agency data. Reach 97% prediction accuracy.

Scoring model for financial company - all files

Experiments with Harmony

ROC-GLM for DataSHIELD

Raisin Class Prediction

Práctica de clasificación con Machine Learning en el dataset del Titanic, abordando exploración de datos, preprocesamiento, selección de métricas y modelos, con el objetivo de analizar detalladamente los resultados obtenidos.

run a multitude of classifiers on you data and get an AUC report

Evaluation of supervised predictions for two-class and multi-class classifiers

Capstone Project for Insurance Premium Default Propensity

Leverage Supervised Machine-learning Techiques to Predict Diabetes from Blood Test

Classification and Regression Performance Metrics library