Spam detection with Naive Bayes

One of the advantages associated with the use of Naive Bayes is the fact that it requires little starting data to begin classifying input data; moreover, the information that progressively adds up contributes to dynamically updating the previous estimates, incrementally improving the forecasting model (unlike, as we saw in the previous paragraph, the algorithm based on decision trees).

Advantages of Naive Bayes for spam detection

The aforementioned features are well suited to the task of spam detection. Without the need to resort to large datasets, in fact, the spam detection algorithms based on Naive Bayes can exploit the emails already present in the inbox, constantly updating the probability...