General naive Bayes classification is a classical machine learning technique to predict a discrete value. There are several variations of naive Bayes (NB) including Categorical NB, Bernoulli NB, ...

This paper utilizes validation data on survey response error in the Current Population Survey to generalize the standard multinomial logit model to allow for spurious ...

The differences between neural network binary classification and multinomial classification are surprisingly tricky. McCaffrey looks at two approaches to implement neural network binary classification ...

The classical maximum entropy (ME) approach to estimating the unknown parameters of a multinomial discrete choice problem, which is equivalent to the maximum likelihood multinomial logit (ML) ...