Which statement is false about Bayesian approaches to classification? a. Bayesia

Question

Which statement is false about Bayesian approaches to classification?

a. Bayesian classification is based on computing the posterior probability as a consequence of a prior probability and a likelihood function derived from a probability model for the data to be observed.

b. One typically generates likelihood functions and prior probabilities from training data, where the class labels of a set of feature vectors are known.

c. Training data can take the form of a histogram computed from localized image windows coinciding with background and foreground classes, where prior probabilities can be estimated either with nonparametric (Parzen windowing) or parametric (Gaussian mixtures) techniques.

d. Expectation–maximization (EM) is a single-iteration method for finding the maximum likelihood estimate of the parameters in statistical models, such as the mean and standard deviation of Gaussian mixture models.

e. None of these statements are false.

Explanation / Answer

Ans : e

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