Regression Tree and Automatic Linear Modeling Techniques were applied this data set to determine the factors affecting grade success of university students and estimate the grade success. SPSS (ver 22 ...

There are roughly a dozen major regression techniques, and each technique has several variations. Among the most common techniques are linear regression, linear ridge regression, k-nearest neighbors ...

For more information on this research see: Comparison and Analysis of the Effectiveness of Linear Regression, Decision Tree, and Random Forest Models for Health Insurance Premium Forecasting.

Explore the complete lifecycle of a machine learning project focused on regression. This repository covers data acquisition, preprocessing, and training with Linear Regression, Decision Tree ...

This data science project aims to predict apartment prices through regression analysis. The dataset used contains information about apartments, and the project involves various steps such as data ...

There are roughly a dozen major regression techniques, and each technique has several variations. Among the most common techniques are linear regression, linear ridge regression, k-nearest neighbors ...

Gradient boosting decision trees (GBDT) is a powerful machine learning algorithm widely used in real-life applications such as online advertising, search ranking, time-series prediction, etc. A GBDT ...