Performance Metric: R-Squared Metric
Explore the R-squared metric to assess regression model performance in AI product management. Understand how to interpret scores, compare models like OLS, random forest, and KNN, and recognize overfitting risks. Gain practical knowledge to select and maintain effective machine learning models for AI products.
Models comparison
We want to go into some applied examples of models and their comparisons to give product managers out there who are unfamiliar with AI/ML performance benchmarks a sense of how we can go about evaluating whether one model is better than another. The following are a few examples of performance metrics that our ML engineers will look at as they evaluate whether or not they’re using optimal models. We’ll notice some of the names are familiar from our previous list of model types.
These comparisons were done on a personal project, which was a model we had created to predict the price of Ether, a form of cryptocurrency.
Ordinary Least Squares Model (OLS)
The first model we wanted to use was an Ordinary Least Squares (OLS) regression model because this is the most straightforward of the linear regression models that we wanted to select to give us a good baseline before we approached other model types. ...