Naive Bayes classification is a machine learning technique that can be used to predict the class of an item based on two or more categorical predictor variables. For example, you might want to predict ...

Naive Bayes classification is especially well suited to problems where the predictor variables are all categorical (strings). And, compared to neural network classifiers, naive Bayes classifications ...

Naive Bayes classification remains a cornerstone of machine learning, renowned for its simplicity, efficiency, and interpretability. This probabilistic approach leverages Bayes’ theorem under the ...

We propose new nonparametric empirical Bayes methods for high-dimensional classification. Our classifiers are designed to approximate the Bayes classifier in a hypothesized hierarchical model, where ...

We explore a Bayesian framework for constructing combinations of classifier outputs, as a means to improving overall classification results. We propose a sequential Bayesian framework to estimate the ...