Null Accuracy

Null accuracy is a baseline measure used in classification problems to evaluate the effectiveness of a model. It represents the accuracy that could be achieved by always predicting the most frequent class in the dataset, without any model training.

Importance of Null Accuracy

Understanding null accuracy is important as it provides a benchmark to compare against the performance of a machine learning model. If a model's accuracy is only slightly better than the null accuracy, it might not be very effective. On the other hand, significantly surpassing the null accuracy indicates that the model is learning meaningful patterns from the data.