Description
Text can be classified with a Bayesian model based on digrams for filtering and categorization tasks. This is useful for developers experimenting with spam filtering, document classification, or lightweight text analysis.
Classifier quality depends on training data and labels. Avoid treating results as objective truth, and be careful with private text used for training or testing.