The following tutorials showcase the linear regression capabilities of the Roseman Labs engine.

In the linear regression tutorial, we build a model using a weather dataset where we use a range of variables in order to predict the temperature. In this tutorial we present both standard linear regression as well as Ridge regression. The tutorial covers all steps from data preprocessing to model training, and evaluation.

The logistic regression tutorial focuses on predicting the probability that a patient develops heart disease, based on a variety lifestyle factors. This tutorial covers many of the same aspects as the linear regression one with the addition of normalization and dummy variable creation. It also presents various model performance metrics in order to gain an understanding of the model’s predictive accuracy.