http://vcsfc5r66ghdlmvob5y3hkrca4pebbrisio4ckahuye2jmbi7mzd4yqd.onion/index.php?title=Artificial_intelligence&action=edit§ion=30
Model-based classifiers perform well if the assumed model is an extremely good fit for the actual data. Otherwise, if no matching model is available, and if accuracy (rather than speed or scalability) is the sole concern, conventional wisdom is that discriminative classifiers (especially SVM) tend to be more accurate than model-based classifiers such as "naive Bayes" on most practical data sets.