A baseline classification uses a naive classification rule such as :
Base Rate (Accuracy of trivially predicting the most-frequent class). (The ZeroR Classifier in Weka) always classify to the largest class– in other words, classify according to the prior.
Random Rate (Accuracy of making a random class assignment, Might apply prior knowledge to assign random distribution)
Naïve Rate (Accuracy of some simple default or pre-existing model (Titanic example: “All females survived”)
It gives a baseline accuracy that must be always checked before choosing a sophisticated classifier. (Simplicity first).
The baseline accuracy is also known as the null rate.