Bayesian Classification and Bayes Network-
Bayesian Classification represent supervised classification method as well as statistical method for calculating classification functions. The Bayesian classification work on probabilities model with different attributes, The probability cross checked at the time of result calculation. It can solve Diagnostic and predictive problems. The Bayesian classification provide the practical learning algorithm and every based knowledge in one solution. Bayesian algorithm best for calculating future outcomes.
P(H/X)=P(X/H).P(H)/P(X) That equation fallows for calculating Bayesian classification.
Bayes Network-
Bayes network shows the possibilities between various variables. The Bayes network allows a subset of the variable conditionally independent device network. Is is a graphical representation of variable conditions that are independent with each other. They gives possibilities of dependent and independent about relationship of variables of graphical data. It gives probability of possible outcomes. It describes the states are related by probability, that model represented States of all possibilities about data with each other and that possibilities are used for future outcomes.