## Discriminant analysis in JMP: meaning of misclassification

New Contributor

Joined:

Aug 29, 2017

Context:

When performing the multivariates analysis called discriminant analysis in JMP, the score Summaries give a number of "Misclassified observations". The user manual pdf "multivariate methods" define the following:

Number Misclassified: Provides the number of observations in the specified set that are incorrectly classified.
Percent Misclassified: Provides the percent of observations in the specified set that are incorrectly classified.

Prob(Pred): Estimated probability of the observation’s predicted classification.

Question

It is unclear to me on what basis an observation is well classified or not. In other words, which this the true criteria behind the "misclassified"?

1) Maybe it is Prob(Pred), but again, how is it calculated?

For instance, is it calculated from the following definitions (given in the "saved formula" section)

1)   qt prior probability of membership for group t

2)  the p(t|y) posterior probability that y belongs to group t   is defined.