2.1.4. Gaussian Naïve Bayes (GNB)

The Gaussian naïve Bayes (GNB) algorithm is a classification technique used in machine learning that leverages a probabilistic approach and the Gaussian distribution to make predictions of input data. GNB treats each attribute variable as independent, enabling it to be trained efficiently in supervised learning and used in complex real-world scenarios. GNB is particularly effective when dealing with high-dimensional data since it assumes independence between features, making it less susceptible to the curse of dimensionality [47].
