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Bayesian Belief Networks A quality control manager has used algorithm C4.5 to come up with rules that classify items based on several input factors....
Bayesian Belief NetworksA quality control manager has used algorithm C4.5 to come up with rules that classify items based on several input factors. The output has two classes -- Accept and Reject.Test results with the rule set indicate that 5% of the good items are classified as Reject and 2% of the bad items classified as Accept.Historical data suggests that one percent of the items are bad. Based on this information, what is the conditional probability that:(i) An item classified as Reject is actually good?(ii) An item classified as Accept is actually bad?Please show detailed process how you obtain the solutions.
