“hidden variables” which are believed to form a relationship. For example, in the case of medical data, a hidden variable may indicate a syndrome, representing a number of symptoms that could characterise a disease (Han et al., 2011). Bayesian Belief Networks are different to naiveBayes ...
Learn how to use the Naive Bayes Classifier for fast and accurate classification in your machine learning projects. Start Reading Now!
Naive Bayes classifiersare linear classifiers that are known for being simple yet very efficient. The probabilistic model of naive Bayes classifiers is based on Bayes’ theorem, and the adjectivenaivecomes from the assumption that the features in a dataset are mutually independent. In practice, the ...
# Create a Naive Bayes classifier. nbc = NaiveBayes() # Load all the training/test ham/spam data. train_hams, train_spams, test_hams, test_spams = nbc.load_data() # Fit the model to the training data. nbc.fit(train_hams, train_spams)...
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