Abstract: This paper examines the usefulness of logistic regression in forecasting the consumer bankruptcy using an imbalanced dataset. It aims to build statistical models that help identify consumers ...

Discover the power of predictive modeling to forecast future outcomes using regression, neural networks, and more for improved business strategies and risk management.

This project aims to predict house prices using the Ames Housing dataset. The goal is to preprocess the data, train a stacking model with multiple base models, and ...

Abstract: In bioinformatics, the rapid development of sequencing technology has enabled us to collect an increasing amount of omics data. Classification based on omics data is one of the central ...

End-to-end ML pipeline that predicts house sale prices on the Ames Housing dataset using ZenML and MLflow. It ingests raw data, handles missing values and outliers, engineers features ...